EasyImage Class
This class contains static properties and methods specific to the EasyImage library.
Namespace: Euresys::Open_eVision
License(s): EasyImage
Properties
Gets/Sets the color of the overlay in the destination image when a BW8 Image is used as overlay source image in functions.
Methods
Performs a locally adaptive threshold on the source image.
Draws an image over an other.
Returns a floating-point statistical parameter extracted from a range of gray levels in an image histogram (most/least frequent value/frequency, min/max value, count, average, standard deviation).
Returns a floating-point statistical parameter extracted from a range of gray levels in an image histogram (most/least frequent value/frequency, min/max value, count, average, standard deviation).
This method is deprecated: Use EImageStatisticsBW8::NumberOfPixelsAboveHighThreshold or EImageStatisticsBW16::NumberOfPixelsAboveHighThreshold instead.
This method is deprecated: Use EImageStatisticsBW8::NumberOfPixelsBetweenThresholds or EImageStatisticsBW16::NumberOfPixelsBetweenThresholds instead.
Prepares a lookup-table image for use for gradient argument computation.
Returns a suitable threshold value for a gray-level image binarization The process of classifying the pixels in an image as belonging to the object of interest (foreground pixels), or not (background pixels). This is a basic technique of image segmentation..
Performs a top-hat filtering on a bilevel image In a bilevel image, pixel value 0 is considered as black, and any other value is considered as white. (closed image minus source image) on a rectangular kernel.
Performs a top-hat filtering on a bilevel image (closed image minus source image) on a quasi-circular kernel.
Performs a closing on a bilevel image (dilation followed by erosion) on a rectangular kernel.
Performs a closing on a bilevel image (dilation followed by erosion) on a quasi-circular kernel.
Performs a dilation on a bilevel image (maximum of the pixel values in a defined neighborhood) on a rectangular kernel. For bilevel images, this maximum can either be 0 (if all pixels are black in the given neighborhood), or the maximum possible pixel value.
Performs a dilation on a bilevel image (maximum of the pixel values in a defined neighborhood) on a quasi-circular kernel.
For bilevel images, this maximum can either be 0 (if all pixels are black in the given neighborhood), or the maximum possible pixel value.
Performs an erosion on a bilevel image (minimum of the pixel values in a defined neighborhood) on a rectangular kernel. For bilevel images, this minimum can either be 0, or the maximum possible pixel value (if all pixels are white in the given neighborhood)
Performs an erosion on a bilevel image (minimum of the pixel values in a defined neighborhood) on a quasi-circular kernel. For bilevel images, this minimum can either be 0, or the maximum possible pixel value (if all pixels are white in the given neighborhood)
Applies a median filter to a bilevel image (median of the gray values in a 3x3 neighborhood).
Computes the morphological gradient of a bilevel image using a rectangular kernel.
Computes the morphological gradient of a bilevel image using a quasi-circular kernel.
Performs an opening on a bilevel image (erosion followed by dilation) on a rectangular kernel.
Performs an opening on a bilevel image (erosion followed by dilation) on a quasi-circular kernel.
Applies a thickening operation on a bilevel image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Applies a thinning operation on a bilevel image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Performs a top-hat filtering on a bilevel image (source image minus open image) on a rectangular kernel.
Performs a top-hat filtering on a bilevel image (source image minus open image) on a quasi-circular kernel.
This method is deprecated: Use EImageStatisticsBW8::GetBinaryMoments or EImageStatisticsBW16::GetBinaryMoments instead.
Performs a top-hat filtering on an image (closed image minus source image) on a rectangular kernel.
Performs a top-hat filtering on an image (closed image minus source image) on a circular kernel.
Performs a closing on an image (dilation followed by erosion) on a rectangular kernel.
Performs a closing on an image (dilation followed by erosion) on a circular kernel.
Transforms the contents of an image to an image of another type.
Turns an 8-bit gray-level image into a YUV 4:2:2 encoded color image.
Computes the Gabor filter response of the source image and stores the result in the destination image.
Applies Gaussian filtering (binomial weights) in rectangular kernel of odd size.
Extracts the edges of an image by summing the absolute values of the Gradient X and Gradient Y derivatives and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along X using a Gradient kernel and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along Y using a Gradient kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 high-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 high-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Performs a convolution in image space, i.e. applies a convolution EKernel.
Takes the second derivative of an image using a 4-neighbor Laplacian kernel and stores the absolute value (magnitude) of the result in the destination image.
Takes the second derivative of an image using an 8-neighbor Laplacian kernel and stores the absolute value (magnitude) of the result in the destination image.
Takes the horizontal second derivative and stores the absolute value (magnitude) of the result in the destination image.
Takes the vertical second derivative and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 low-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 low-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 low-pass kernel.
Extracts the edges of an image by summing the absolute values of the Prewitt X and Prewitt Y derivatives and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along X using a Prewitt kernel and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along Y using a Prewitt kernel and stores the absolute value (magnitude) of the result in the destination image.
The Roberts edge extraction filter is based on a 2x2 kernel.
Extracts the edges of an image by summing the absolute values of the Sobel X and Sobel Y derivatives.
Derives an image along X using a Sobel kernel and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along Y using a Sobel kernel and stores the absolute value (magnitude) of the result in the destination image.
Performs a convolution in image space, i.e. applies a square symmetric convolution kernel of size 3x3, 5x5 or 7x7.
Applies strong low-pass filtering to an image by using a uniform rectangular kernel of odd size.
Copies a source image or a constant in a destination image.
Cumulates histogram values in another histogram.
This function converts an interlaced image into two separate non-interlaced images. The first output, out1, will contain the even lines, while the second output, out2, will contain the odd lines. The resulting images can optionally be interpolated to match the dimensions of the original image. If interpolation is not applied, the height of each output image must be half the height of the input image. Otherwise, the height of each output image must be of the same height of the input image. If enabled, interpolation will be linear.
Performs a dilation on an image (maximum of the gray values in a defined neighborhood) on a rectangular kernel.
Performs a dilation on an image (maximum of the gray values in a defined neighborhood) on a circular kernel.
Computes the morphological distance function on a binary image (0 for black, non 0 for white).
Converts an image by setting all pixels below the low threshold to a low value, all pixels above the high threshold to a high value, and the remaining pixels to an intermediate value.
Equalizes an image histogram (the gray levels are re-mapped so that the histogram becomes as close to uniform as possible).
Performs an erosion on an image (minimum of the gray values in a defined neighborhood) on a rectangular kernel.
Performs an erosion on an image (minimum of the gray values in a defined neighborhood) on a circular kernel.
Flip an image around either the vertical axis, the horizontal axis or both.
Returns a measure of the focusing of an image by computing the total gradient energy.
Transforms an image, applying a gain and offset to all pixels.
Transforms an image, applying a gain and offset to all pixels.
Extracts the frame of given parity from an image.
Detects peaks in a gray-level profile. Maxima as well as minima are considered.
Computes the (scalar) gradient image derived from a given source image.
This method is deprecated: Use EImageStatisticsBW8::GravityCenterOfPixelsAboveHighThreshold or EImageStatisticsBW16::GravityCenterOfPixelsAboveHighThreshold instead.
Fuses two images using HDR principles.
Computes the histogram of an image (count of each gray-level value).
Determines an appropriate threshold level based on the histogram contents, using an automatic threshold mode.
Determines an appropriate threshold level based on the histogram contents, using an automatic threshold mode.
Apply the morphological hit-and-miss transform to detect a particular pattern of foreground and background pixels in a BW8, BW16 or C24 image/ROI.
Mirrors an image horizontally (the columns are swapped).
Copies the pixel values along a given line segment (arbitrarily oriented) to a vector.
Given a path described by coordinates in a path vector, copies the corresponding pixel values into the same vector.
This function converts two non-interlaced images into one interlaced image. The first input, in1, should contain the even lines, while the second input, in2, should contain the odd lines. Input images should have the same width, but a height that is half the height of the destination image.
Computes a suitable threshold value for a histogram.
Computes a suitable threshold value for a histogram.
Applies a general affine transformation.
Copies the pixel values from a vector or a constant to the pixels of a given line segment (arbitrarily oriented).
Computes the average in a rectangular window centered on every pixel.
Computes the standard deviation in a rectangular window centered on every pixel.
Transforms the gray levels of an image, using a lookup table stored in a vector (of unsigned values).
Determines the optimal shift amplitude by comparing two successive lines of the image.
Applies a median filter to an image (median of the gray values in a neighborhood). Kernel may be of an arbitrary size.
Prepares a lookup-table image for use for gradient magnitude computation.
Computes the morphological gradient of an image using a rectangular kernel.
Computes the morphological gradient of an image using a circular kernel.
Normalizes an image, i.e. applies a linear transform to the gray levels so that their average and standard deviation are imposed.
Transforms an image, applying a gain and offset to all pixels.
Performs an opening on an image (erosion followed by dilation) on a rectangular kernel.
Performs an opening on an image (erosion followed by dilation) on a circular kernel.
Applies the desired arithmetic or logic pixel-wise operator between two images or constants.
Overlays an image on the top of a color image, at a given position.
Given a path described by coordinates in a path vector, copies the pixel values from the path vector to the corresponding image pixels.
This method is deprecated: Use EImageStatisticsBW8::PixelAverage, EImageStatisticsBW16::PixelAverage or EImageStatisticsC24::PixelAverage instead.
Counts the number of pixels differing between two images.
This method is deprecated: Use EImageStatisticsBW8 or EImageStatisticsBW16 instead.
Computes the maximum gray-level value in an image.
Computes the maximum gray-level value in an image.
Computes the maximum gray-level value in an image.
Computes the minimum gray-level value in an image.
Computes the minimum gray-level value in an image.
Computes the minimum gray-level value in an image.
This method is deprecated: Use EImageStatisticsBW8, EImageStatisticsBW16 or EImageStatisticsC24 instead.
This method is deprecated: Use EImageStatisticsBW16 instead.
This method is deprecated: Use EImageStatisticsBW8 instead.
This method is deprecated: Use EImageStatisticsBW8::PixelStdDev, EImageStatisticsBW16::PixelStdDev or EImageStatisticsC24::PixelStdDev instead.
This method is deprecated: Use EImageStatisticsBW8::PixelVariance, EImageStatisticsBW16::PixelVariance or EImageStatisticsC24::PixelVariances instead.
Computes the first derivative of a profile extracted from a gray-level image.
Projects an image horizontally onto a column.
Projects an image vertically onto a row.
Shifts one frame of the image horizontally.
Rebuilds one frame of the image by interpolation between the lines of the other frame.
Applies stronger noise reduction to small variations and conversely.
Registers an image by realigning one, two or three pivot points to reference positions.
Resize an image. The dimension to resize to are infered by the size of the destination image.
Computes the root-mean-square amplitude of noise, by comparing a given image to a reference image.
Rotate an image by an increment of a quarter of a turn (right angle).
Re-scales an image by an arbitrary factor and/or rotates it by an arbitrary angle.
Prepares suitable warp images for use with function EasyImage::Warp to unwarp a circular ring-wedge shape into a straight rectangle.
This is a cartesian to polar image conversion function.
See also EasyImage::SetInvCircleWarp.
Replaces the frame of given parity in an image.
Prepares suitable warp images for use with function EasyImage::Warp to unwarp a straight rectangle into a circular ring-wedge shape.
This is a polar to cartesian image conversion function.
See also EasyImage::SetCircleWarp.
Pre-compute the required non-linear transfer function for noise reduction by recursive temporal averaging.
Prepares a lookup-table for image equalization, using an image histogram.
Prepares suitable inverse warp images for use with function EasyImage::Warp to unwarp an invertible LUT given by the warpImageX and warpImageY.
Resizes an image to a smaller size. Pre-filtering is applied to avoid aliasing.
Computes the signal to noise ratio, in dB, by comparing a given image to a reference image.
Interchanges the even and odd rows of an image.
Applies a thickening operation on an image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Applies a thinning operation on an image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Computes the two threshold values used to separate the pixels of an image in three classes.
Binarize an image by setting pixels to two different possible values in a destination image, according to their value in a source image.
Transpose an image.
Computes the threshold value used to separate the pixels of an image in two classes.
Shading correction is the process of transforming the gray or color component values of an image, using one or two reference images or vectors.
Mirrors an image vertically (the rows are swapped).
Transforms an image so that each pixels are moved to the locations specified in the "warp" images used as look-up tables.
This method is deprecated: Use EImageStatisticsBW8::GetWeightedMoments or EImageStatisticsBW16::GetWeightedMoments.
Performs a top-hat filtering on an image (source image minus open image) on a rectangular kernel.
Performs a top-hat filtering on an image (source image minus open image) on a circular kernel.
EasyImage Class
This class contains static properties and methods specific to the EasyImage library.
Namespace: Euresys.Open_eVision
License(s): EasyImage
Properties
Returns the color of the overlay in the destination image when an EBW8 image is used as overlay source image in functions:
Methods
Performs a locally adaptive threshold on the source image.
Draws an image over an other.
Returns a floating-point statistical parameter extracted from a range of gray levels in an image histogram (most/least frequent value/frequency, min/max value, count, average, standard deviation).
Returns a floating-point statistical parameter extracted from a range of gray levels in an image histogram (most/least frequent value/frequency, min/max value, count, average, standard deviation).
This method is deprecated: Use EImageStatisticsBW8.NumberOfPixelsAboveHighThreshold or EImageStatisticsBW16.NumberOfPixelsAboveHighThreshold instead.
This method is deprecated: Use EImageStatisticsBW8.NumberOfPixelsBetweenThresholds or EImageStatisticsBW16.NumberOfPixelsBetweenThresholds instead.
Prepares a lookup-table image for use for gradient argument computation.
Returns a suitable threshold value for a gray-level image binarization.
Performs a top-hat filtering on a bilevel image (closed image minus source image) on a rectangular kernel.
Performs a top-hat filtering on a bilevel image (closed image minus source image) on a quasi-circular kernel.
Performs a closing on a bilevel image (dilation followed by erosion) on a rectangular kernel.
Performs a closing on a bilevel image (dilation followed by erosion) on a quasi-circular kernel.
Performs a dilation on a bilevel image (maximum of the pixel values in a defined neighborhood) on a rectangular kernel. For bilevel images, this maximum can either be 0 (if all pixels are black in the given neighborhood), or the maximum possible pixel value.
Performs a dilation on a bilevel image (maximum of the pixel values in a defined neighborhood) on a quasi-circular kernel.
For bilevel images, this maximum can either be 0 (if all pixels are black in the given neighborhood), or the maximum possible pixel value.
Performs an erosion on a bilevel image (minimum of the pixel values in a defined neighborhood) on a rectangular kernel. For bilevel images, this minimum can either be 0, or the maximum possible pixel value (if all pixels are white in the given neighborhood)
Performs an erosion on a bilevel image (minimum of the pixel values in a defined neighborhood) on a quasi-circular kernel. For bilevel images, this minimum can either be 0, or the maximum possible pixel value (if all pixels are white in the given neighborhood)
Applies a median filter to a bilevel image (median of the gray values in a 3x3 neighborhood).
Computes the morphological gradient of a bilevel image using a rectangular kernel.
Computes the morphological gradient of a bilevel image using a quasi-circular kernel.
Performs an opening on a bilevel image (erosion followed by dilation) on a rectangular kernel.
Performs an opening on a bilevel image (erosion followed by dilation) on a quasi-circular kernel.
Applies a thickening operation on a bilevel image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Applies a thinning operation on a bilevel image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Performs a top-hat filtering on a bilevel image (source image minus open image) on a rectangular kernel.
Performs a top-hat filtering on a bilevel image (source image minus open image) on a quasi-circular kernel.
This method is deprecated: Use EImageStatisticsBW8.GetBinaryMoments or EImageStatisticsBW16.GetBinaryMoments instead.
Performs a top-hat filtering on an image (closed image minus source image) on a rectangular kernel.
Performs a top-hat filtering on an image (closed image minus source image) on a circular kernel.
Performs a closing on an image (dilation followed by erosion) on a rectangular kernel.
Performs a closing on an image (dilation followed by erosion) on a circular kernel.
Follows the contour of an object.
Transforms the contents of an image to an image of another type.
Turns an 8-bit gray-level image into a YUV 4:2:2 encoded color image.
Computes the Gabor filter response of the source image and stores the result in the destination image.
Applies Gaussian filtering (binomial weights) in rectangular kernel of odd size.
Extracts the edges of an image by summing the absolute values of the Gradient X and Gradient Y derivatives and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along X using a Gradient kernel and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along Y using a Gradient kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 high-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 high-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Performs a convolution in image space, i.e. applies a convolution EKernel.
Takes the second derivative of an image using a 4-neighbor Laplacian kernel and stores the absolute value (magnitude) of the result in the destination image.
Takes the second derivative of an image using an 8-neighbor Laplacian kernel and stores the absolute value (magnitude) of the result in the destination image.
Takes the horizontal second derivative and stores the absolute value (magnitude) of the result in the destination image.
Takes the vertical second derivative and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 low-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 low-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 low-pass kernel.
Extracts the edges of an image by summing the absolute values of the Prewitt X and Prewitt Y derivatives and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along X using a Prewitt kernel and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along Y using a Prewitt kernel and stores the absolute value (magnitude) of the result in the destination image.
The Roberts edge extraction filter is based on a 2x2 kernel.
Extracts the edges of an image by summing the absolute values of the Sobel X and Sobel Y derivatives.
Derives an image along X using a Sobel kernel and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along Y using a Sobel kernel and stores the absolute value (magnitude) of the result in the destination image.
Performs a convolution in image space, i.e. applies a square symmetric convolution kernel of size 3x3, 5x5 or 7x7.
Applies strong low-pass filtering to an image by using a uniform rectangular kernel of odd size.
Copies a source image or a constant in a destination image.
Cumulates histogram values in another histogram.
This function converts an interlaced image into two separate non-interlaced images. The first output, out1, will contain the even lines, while the second output, out2, will contain the odd lines. The resulting images can optionally be interpolated to match the dimensions of the original image. If interpolation is not applied, the height of each output image must be half the height of the input image. Otherwise, the height of each output image must be of the same height of the input image. If enabled, interpolation will be linear.
Performs a dilation on an image (maximum of the gray values in a defined neighborhood) on a rectangular kernel.
Performs a dilation on an image (maximum of the gray values in a defined neighborhood) on a circular kernel.
Computes the morphological distance function on a binary image (0 for black, non 0 for white).
Converts an image by setting all pixels below the low threshold to a low value, all pixels above the high threshold to a high value, and the remaining pixels to an intermediate value.
Equalizes an image histogram (the gray levels are re-mapped so that the histogram becomes as close to uniform as possible).
Performs an erosion on an image (minimum of the gray values in a defined neighborhood) on a rectangular kernel.
Performs an erosion on an image (minimum of the gray values in a defined neighborhood) on a circular kernel.
Flip an image around either the vertical axis, the horizontal axis or both.
Returns a measure of the focusing of an image by computing the total gradient energy.
Transforms an image, applying a gain and offset to all pixels.
Transforms an image, applying a gain and offset to all pixels.
Extracts the frame of given parity from an image.
Detects peaks in a gray-level profile. Maxima as well as minima are considered.
Computes the (scalar) gradient image derived from a given source image.
This method is deprecated: Use EImageStatisticsBW8.GravityCenterOfPixelsAboveHighThreshold or EImageStatisticsBW16.GravityCenterOfPixelsAboveHighThreshold instead.
Fuses two images using HDR principles.
Computes the histogram of an image (count of each gray-level value).
Determines an appropriate threshold level based on the histogram contents, using an automatic threshold mode.
Determines an appropriate threshold level based on the histogram contents, using an automatic threshold mode.
Apply the morphological hit-and-miss transform to detect a particular pattern of foreground and background pixels in a BW8, BW16 or C24 image/ROI.
Mirrors an image horizontally (the columns are swapped).
Copies the pixel values along a given line segment (arbitrarily oriented) to a vector.
Given a path described by coordinates in a path vector, copies the corresponding pixel values into the same vector.
This function converts two non-interlaced images into one interlaced image. The first input, in1, should contain the even lines, while the second input, in2, should contain the odd lines. Input images should have the same width, but a height that is half the height of the destination image.
Computes a suitable threshold value for a histogram.
Computes a suitable threshold value for a histogram.
Applies a general affine transformation.
Copies the pixel values from a vector or a constant to the pixels of a given line segment (arbitrarily oriented).
Computes the average in a rectangular window centered on every pixel.
Computes the standard deviation in a rectangular window centered on every pixel.
Transforms the gray levels of an image, using a lookup table stored in a vector (of unsigned values).
Determines the optimal shift amplitude by comparing two successive lines of the image.
Applies a median filter to an image (median of the gray values in a neighborhood). Kernel may be of an arbitrary size.
Prepares a lookup-table image for use for gradient magnitude computation.
Computes the morphological gradient of an image using a rectangular kernel.
Computes the morphological gradient of an image using a circular kernel.
Normalizes an image, i.e. applies a linear transform to the gray levels so that their average and standard deviation are imposed.
Transforms an image, applying a gain and offset to all pixels.
Performs an opening on an image (erosion followed by dilation) on a rectangular kernel.
Performs an opening on an image (erosion followed by dilation) on a circular kernel.
Applies the desired arithmetic or logic pixel-wise operator between two images or constants.
Overlays an image on the top of a color image, at a given position.
Given a path described by coordinates in a path vector, copies the pixel values from the path vector to the corresponding image pixels.
This method is deprecated: Use EImageStatisticsBW8.PixelAverage, EImageStatisticsBW16.PixelAverage or EImageStatisticsC24.PixelAverage instead.
Counts the number of pixels differing between two images.
This method is deprecated: Use EImageStatisticsBW8 or EImageStatisticsBW16 instead.
Computes the maximum gray-level value in an image.
Computes the maximum gray-level value in an image.
Computes the maximum gray-level value in an image.
Computes the minimum gray-level value in an image.
Computes the minimum gray-level value in an image.
Computes the minimum gray-level value in an image.
This method is deprecated: Use EImageStatisticsBW8, EImageStatisticsBW16 or EImageStatisticsC24 instead.
This method is deprecated: Use EImageStatisticsBW16 instead.
This method is deprecated: Use EImageStatisticsBW8 instead.
This method is deprecated: Use EImageStatisticsBW8.PixelStdDev, EImageStatisticsBW16.PixelStdDev or EImageStatisticsC24.PixelStdDev instead.
This method is deprecated: Use EImageStatisticsBW8.PixelVariance, EImageStatisticsBW16.PixelVariance or EImageStatisticsC24.PixelVariances instead.
Computes the first derivative of a profile extracted from a gray-level image.
Projects an image horizontally onto a column.
Projects an image vertically onto a row.
Shifts one frame of the image horizontally.
Rebuilds one frame of the image by interpolation between the lines of the other frame.
Applies stronger noise reduction to small variations and conversely.
Registers an image by realigning one, two or three pivot points to reference positions.
Resize an image. The dimension to resize to are infered by the size of the destination image.
Computes the root-mean-square amplitude of noise, by comparing a given image to a reference image.
Rotate an image by an increment of a quarter of a turn (right angle).
Re-scales an image by an arbitrary factor and/or rotates it by an arbitrary angle.
Prepares suitable warp images for use with function EasyImage.Warp to unwarp a circular ring-wedge shape into a straight rectangle.
This is a cartesian to polar image conversion function.
See also EasyImage.SetInvCircleWarp.
Replaces the frame of given parity in an image.
Prepares suitable warp images for use with function EasyImage.Warp to unwarp a straight rectangle into a circular ring-wedge shape.
This is a polar to cartesian image conversion function.
See also EasyImage.SetCircleWarp.
Pre-compute the required non-linear transfer function for noise reduction by recursive temporal averaging.
Prepares a lookup-table for image equalization, using an image histogram.
Prepares suitable inverse warp images for use with function EasyImage.Warp to unwarp an invertible LUT given by the warpImageX and warpImageY.
Resizes an image to a smaller size. Pre-filtering is applied to avoid aliasing.
Computes the signal to noise ratio, in dB, by comparing a given image to a reference image.
Interchanges the even and odd rows of an image.
Applies a thickening operation on an image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Applies a thinning operation on an image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Computes the two threshold values used to separate the pixels of an image in three classes.
Binarize an image by setting pixels to two different possible values in a destination image, according to their value in a source image.
Transpose an image.
Computes the threshold value used to separate the pixels of an image in two classes.
Shading correction is the process of transforming the gray or color component values of an image, using one or two reference images or vectors.
Mirrors an image vertically (the rows are swapped).
Transforms an image so that each pixels are moved to the locations specified in the "warp" images used as look-up tables.
This method is deprecated: Use EImageStatisticsBW8.GetWeightedMoments or EImageStatisticsBW16.GetWeightedMoments.
Performs a top-hat filtering on an image (source image minus open image) on a rectangular kernel.
Performs a top-hat filtering on an image (source image minus open image) on a circular kernel.
EasyImage Class
This class contains static properties and methods specific to the EasyImage library.
Module: open_evision
License(s): EasyImage
Properties
Gets/Sets the color of the overlay in the destination image when a BW8 Image is used as overlay source image in functions.
Methods
Performs a locally adaptive threshold on the source image.
Draws an image over an other.
Returns a floating-point statistical parameter extracted from a range of gray levels in an image histogram (most/least frequent value/frequency, min/max value, count, average, standard deviation).
Returns a floating-point statistical parameter extracted from a range of gray levels in an image histogram (most/least frequent value/frequency, min/max value, count, average, standard deviation).
Prepares a lookup-table image for use for gradient argument computation.
Returns a suitable threshold value for a gray-level image binarization.
Performs a top-hat filtering on a bilevel image (closed image minus source image) on a rectangular kernel.
Performs a top-hat filtering on a bilevel image (closed image minus source image) on a quasi-circular kernel.
Performs a closing on a bilevel image (dilation followed by erosion) on a rectangular kernel.
Performs a closing on a bilevel image (dilation followed by erosion) on a quasi-circular kernel.
Performs a dilation on a bilevel image (maximum of the pixel values in a defined neighborhood) on a rectangular kernel. For bilevel images, this maximum can either be 0 (if all pixels are black in the given neighborhood), or the maximum possible pixel value.
Performs a dilation on a bilevel image (maximum of the pixel values in a defined neighborhood) on a quasi-circular kernel.
For bilevel images, this maximum can either be 0 (if all pixels are black in the given neighborhood), or the maximum possible pixel value.
Performs an erosion on a bilevel image (minimum of the pixel values in a defined neighborhood) on a rectangular kernel. For bilevel images, this minimum can either be 0, or the maximum possible pixel value (if all pixels are white in the given neighborhood)
Performs an erosion on a bilevel image (minimum of the pixel values in a defined neighborhood) on a quasi-circular kernel. For bilevel images, this minimum can either be 0, or the maximum possible pixel value (if all pixels are white in the given neighborhood)
Applies a median filter to a bilevel image (median of the gray values in a 3x3 neighborhood).
Computes the morphological gradient of a bilevel image using a rectangular kernel.
Computes the morphological gradient of a bilevel image using a quasi-circular kernel.
Performs an opening on a bilevel image (erosion followed by dilation) on a rectangular kernel.
Performs an opening on a bilevel image (erosion followed by dilation) on a quasi-circular kernel.
Applies a thickening operation on a bilevel image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Applies a thinning operation on a bilevel image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Performs a top-hat filtering on a bilevel image (source image minus open image) on a rectangular kernel.
Performs a top-hat filtering on a bilevel image (source image minus open image) on a quasi-circular kernel.
Performs a top-hat filtering on an image (closed image minus source image) on a rectangular kernel.
Performs a top-hat filtering on an image (closed image minus source image) on a circular kernel.
Performs a closing on an image (dilation followed by erosion) on a rectangular kernel.
Performs a closing on an image (dilation followed by erosion) on a circular kernel.
Follows the contour of an object.
Transforms the contents of an image to an image of another type.
Turns an 8-bit gray-level image into a YUV 4:2:2 encoded color image.
Computes the Gabor filter response of the source image and stores the result in the destination image.
Applies Gaussian filtering (binomial weights) in rectangular kernel of odd size.
Extracts the edges of an image by summing the absolute values of the Gradient X and Gradient Y derivatives and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along X using a Gradient kernel and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along Y using a Gradient kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 high-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 high-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Performs a convolution in image space, i.e. applies a convolution EKernel.
Takes the second derivative of an image using a 4-neighbor Laplacian kernel and stores the absolute value (magnitude) of the result in the destination image.
Takes the second derivative of an image using an 8-neighbor Laplacian kernel and stores the absolute value (magnitude) of the result in the destination image.
Takes the horizontal second derivative and stores the absolute value (magnitude) of the result in the destination image.
Takes the vertical second derivative and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 low-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 low-pass kernel and stores the absolute value (magnitude) of the result in the destination image.
Filters an image using a 3x3 low-pass kernel.
Extracts the edges of an image by summing the absolute values of the Prewitt X and Prewitt Y derivatives and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along X using a Prewitt kernel and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along Y using a Prewitt kernel and stores the absolute value (magnitude) of the result in the destination image.
The Roberts edge extraction filter is based on a 2x2 kernel.
Extracts the edges of an image by summing the absolute values of the Sobel X and Sobel Y derivatives.
Derives an image along X using a Sobel kernel and stores the absolute value (magnitude) of the result in the destination image.
Derives an image along Y using a Sobel kernel and stores the absolute value (magnitude) of the result in the destination image.
Performs a convolution in image space, i.e. applies a square symmetric convolution kernel of size 3x3, 5x5 or 7x7.
Applies strong low-pass filtering to an image by using a uniform rectangular kernel of odd size.
Copies a source image or a constant in a destination image.
Cumulates histogram values in another histogram.
This function converts an interlaced image into two separate non-interlaced images. The first output, out1, will contain the even lines, while the second output, out2, will contain the odd lines. The resulting images can optionally be interpolated to match the dimensions of the original image. If interpolation is not applied, the height of each output image must be half the height of the input image. Otherwise, the height of each output image must be of the same height of the input image. If enabled, interpolation will be linear.
Performs a dilation on an image (maximum of the gray values in a defined neighborhood) on a rectangular kernel.
Performs a dilation on an image (maximum of the gray values in a defined neighborhood) on a circular kernel.
Computes the morphological distance function on a binary image (0 for black, non 0 for white).
Converts an image by setting all pixels below the low threshold to a low value, all pixels above the high threshold to a high value, and the remaining pixels to an intermediate value.
Equalizes an image histogram (the gray levels are re-mapped so that the histogram becomes as close to uniform as possible).
Performs an erosion on an image (minimum of the gray values in a defined neighborhood) on a rectangular kernel.
Performs an erosion on an image (minimum of the gray values in a defined neighborhood) on a circular kernel.
Flip an image around either the vertical axis, the horizontal axis or both.
Returns a measure of the focusing of an image by computing the total gradient energy.
Transforms an image, applying a gain and offset to all pixels.
Transforms an image, applying a gain and offset to all pixels.
Extracts the frame of given parity from an image.
Detects peaks in a gray-level profile. Maxima as well as minima are considered.
Computes the (scalar) gradient image derived from a given source image.
Fuses two images using HDR principles.
Computes the histogram of an image (count of each gray-level value).
Determines an appropriate threshold level based on the histogram contents, using an automatic threshold mode.
Determines an appropriate threshold level based on the histogram contents, using an automatic threshold mode.
Apply the morphological hit-and-miss transform to detect a particular pattern of foreground and background pixels in a BW8, BW16 or C24 image/ROI.
Mirrors an image horizontally (the columns are swapped).
Copies the pixel values along a given line segment (arbitrarily oriented) to a vector.
Given a path described by coordinates in a path vector, copies the corresponding pixel values into the same vector.
This function converts two non-interlaced images into one interlaced image. The first input, in1, should contain the even lines, while the second input, in2, should contain the odd lines. Input images should have the same width, but a height that is half the height of the destination image.
Computes a suitable threshold value for a histogram.
Computes a suitable threshold value for a histogram.
Applies a general affine transformation.
Copies the pixel values from a vector or a constant to the pixels of a given line segment (arbitrarily oriented).
Computes the average in a rectangular window centered on every pixel.
Computes the standard deviation in a rectangular window centered on every pixel.
Transforms the gray levels of an image, using a lookup table stored in a vector (of unsigned values).
Determines the optimal shift amplitude by comparing two successive lines of the image.
Applies a median filter to an image (median of the gray values in a neighborhood). Kernel may be of an arbitrary size.
Prepares a lookup-table image for use for gradient magnitude computation.
Computes the morphological gradient of an image using a rectangular kernel.
Computes the morphological gradient of an image using a circular kernel.
Normalizes an image, i.e. applies a linear transform to the gray levels so that their average and standard deviation are imposed.
Transforms an image, applying a gain and offset to all pixels.
Performs an opening on an image (erosion followed by dilation) on a rectangular kernel.
Performs an opening on an image (erosion followed by dilation) on a circular kernel.
Applies the desired arithmetic or logic pixel-wise operator between two images or constants.
Overlays an image on the top of a color image, at a given position.
Given a path described by coordinates in a path vector, copies the pixel values from the path vector to the corresponding image pixels.
Counts the number of pixels differing between two images.
Computes the maximum gray-level value in an image.
Computes the maximum gray-level value in an image.
Computes the maximum gray-level value in an image.
Computes the minimum gray-level value in an image.
Computes the minimum gray-level value in an image.
Computes the minimum gray-level value in an image.
Computes the first derivative of a profile extracted from a gray-level image.
Projects an image horizontally onto a column.
Projects an image vertically onto a row.
Shifts one frame of the image horizontally.
Rebuilds one frame of the image by interpolation between the lines of the other frame.
Applies stronger noise reduction to small variations and conversely.
Registers an image by realigning one, two or three pivot points to reference positions.
Resize an image. The dimension to resize to are infered by the size of the destination image.
Computes the root-mean-square amplitude of noise, by comparing a given image to a reference image.
Rotate an image by an increment of a quarter of a turn (right angle).
Re-scales an image by an arbitrary factor and/or rotates it by an arbitrary angle.
Prepares suitable warp images for use with function EasyImage.Warp to unwarp a circular ring-wedge shape into a straight rectangle.
This is a cartesian to polar image conversion function.
See also EasyImage.SetInvCircleWarp.
Replaces the frame of given parity in an image.
Prepares suitable warp images for use with function EasyImage.Warp to unwarp a straight rectangle into a circular ring-wedge shape.
This is a polar to cartesian image conversion function.
See also EasyImage.SetCircleWarp.
Pre-compute the required non-linear transfer function for noise reduction by recursive temporal averaging.
Prepares a lookup-table for image equalization, using an image histogram.
Prepares suitable inverse warp images for use with function EasyImage.Warp to unwarp an invertible LUT given by the warpImageX and warpImageY.
Resizes an image to a smaller size. Pre-filtering is applied to avoid aliasing.
Computes the signal to noise ratio, in dB, by comparing a given image to a reference image.
Interchanges the even and odd rows of an image.
Applies a thickening operation on an image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Applies a thinning operation on an image, using a 3x3 kernel. The method returns the number of iterations actually performed.
Computes the two threshold values used to separate the pixels of an image in three classes.
Binarize an image by setting pixels to two different possible values in a destination image, according to their value in a source image.
Transpose an image.
Computes the threshold value used to separate the pixels of an image in two classes.
Shading correction is the process of transforming the gray or color component values of an image, using one or two reference images or vectors.
Mirrors an image vertically (the rows are swapped).
Transforms an image so that each pixels are moved to the locations specified in the "warp" images used as look-up tables.
Performs a top-hat filtering on an image (source image minus open image) on a rectangular kernel.
Performs a top-hat filtering on an image (source image minus open image) on a circular kernel.