Rotationally impervious feature extraction for optical character recognition
First Claim
1. A feature-based optical character recognition system for extracting features from an individual character image segmented from a document image, comprising:
- radial intercept feature extraction means for counting a number of intercepts between at least one of a plurality of circles of predetermined radii and boundary transitions in said character image;
transition point location feature extraction means for determining for each transition point in said image an identity of a pair of regions in a grid superimposed on said character image nearest the transition point, whereby said number of intercepts and said identity of said pair of regions comprise an input data string; and
feature-based recognition means for comparing said input data string with a set of reference data strings corresponding to a set of known symbols.
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Abstract
A feature-based optical character recognition system, employing a feature-based recognition device such as a neural network or an absolute distance measure device, extracts a set of features from segmented character images in a document, at least some of the extracted features being at least nearly impervious to rotation or skew of the document image, so as to enhance the reliability of the system. One rotationally invariant feature extracted by the system is the number of intercepts between boundary transitions in the image with at least a selected one of a plurality of radii centered at the centroid of the character in the image.
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Citations
24 Claims
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1. A feature-based optical character recognition system for extracting features from an individual character image segmented from a document image, comprising:
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radial intercept feature extraction means for counting a number of intercepts between at least one of a plurality of circles of predetermined radii and boundary transitions in said character image; transition point location feature extraction means for determining for each transition point in said image an identity of a pair of regions in a grid superimposed on said character image nearest the transition point, whereby said number of intercepts and said identity of said pair of regions comprise an input data string; and feature-based recognition means for comparing said input data string with a set of reference data strings corresponding to a set of known symbols. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A feature-based optical character recognition method for extracting features from an individual character image segmented from a document image, comprising:
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counting a number of intercepts between at least one of a plurality of circles of predetermined radii in said character image and boundary transitions in said character image; determining for each transition point in said image an identity of a pair of regions in a grid superimposed on said character image nearest the transition point, whereby said number of intercepts and said identity of said pair of regions comprise an input data string; and comparing said input data string with a set of reference data strings corresponding to a set of known symbols. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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Specification