Constructs a matching context.

Toggle advanced learning.

Contrast mode.

Correlation mode.

"Don't care" threshold.

Whether to remove bad candidates in the early phases of the processing or not. Enabled by default.

Sets/Gets the extension of the matching ROI, i.e. puts the horizontal and vertical distances, in pixels, that the found pattern occurrences may fall outside the matching ROI. Such occurrences partially outside the ROI have their score corrected by the ratio between the pattern area outside the ROI and the pattern area inside.

Filtering mode.

Index of the last reduction.

Minimum score applied as a selection criterion in the early stages of the matching process.

Interpolation mode.

Flag indicating whether isotropic (as opposed to anisotropic) scaling is used.

Indicates whether a ERegion was used alongside the last learned pattern. Returns false if no learning was performed.

Time-out for the EMatcher.LearnPattern and EMatcher.LearnPatterns methods.

Time-out for the EMatcher.Match method.

Maximum angle, in the current angle unit.

Maximum number of positions at the first stage of the matching process.

Overlapping tolerance

Maximum number of positions.

Maximum scale factor for isotropic scaling.

Maximum horizontal scale factor for anisotropic scaling.

Maximum vertical scale factor for anisotropic scaling.

Minimum angle, in the current angle unit.

Minimum reduced area parameter.

Minimum scale factor for isotropic scaling.

Minimum horizontal scale factor for anisotropic scaling.

Minimum vertical scale factor for anisotropic scaling.

Minimum score.

Indicates the number of patterns learnt. 0 is returned if no learning was performed.

Number of reduction steps used in the matching process.

Learned pattern height.

When multiple patterns are learned, the height of the first pattern is returned. Use EMatcher.GetPatternHeight for other learnt patterns.

Returns true after a learning operation has been successfully performed, indicating that the EMatcher object is ready for matching, and false otherwise.

Pixel type of the learned pattern.

Learned pattern width.

When multiple patterns are learned, the width of the first pattern is returned. Use EMatcher.GetPatternWidth for other learnt patterns.

Gets/Sets the physical pixel dimensions.

Version number of the EMatcher object.

Constructs a matching context.

Releases the pointer to the image object that has been passed to the EMatcher object.

Copies the learned pattern in the supplied image. If no pattern has been learned, an exception with code EError.NoPatternLearnt will be thrown.

Copies all the data of the current EMatcher object into another EMatcher object and returns it.

Gets the angle step used at the given reduction.

Learned pattern height.

Learned pattern width.

Gets the scale step used at the given reduction.

When multiple patterns are learned, the scale step corresponding to the first pattern at the given reduction is returned.

Gets the scale step used on the X axis at the given reduction.

When multiple patterns are learned, the scale X step corresponding to the first pattern at the given reduction is returned.

Gets the scale step used on the Y axis at the given reduction.

When multiple patterns are learned, the scale Y step corresponding to the first pattern at the given reduction is returned.

Learns a pattern to subsequently match in an image.

Learns multiple (at least 2) patterns.

Loads the EMatcher. The given ESerializer must have been created for reading.

Matches the pattern against an image.

Saves the EMatcher. The given ESerializer must have been created for writing.