Character segmentation using an associative memory for optical character recognition
First Claim
1. Character segmentation apparatus for an optical character recognition system for segmenting individual character images in an image of a document comprising plural characters, prior to performing character identification, said image of a document comprising an array of pixels, said apparatus comprising:
- kernel means for capturing, in said image of a document, a sub-image framed within a window having an area corresponding to an area occupied by an individual character of said document, said window being movable in said image of a document in pixel-by-pixel steps whereby said kernel means captures a sub-image for each step of said window;
associative memory means for responding to said sub-image by producing a corresponding one of a set of training images of known characters with which said associative memory has been trained; and
sensor means, responsive to said associative memory means producing said corresponding one of a set of training images of known characters, for determining whether said sub-image is the image of an individual character, and segmenting said sub-image as an unidentified individual character image in response to said sub-image corresponding to the image of an individual character.
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Abstract
Character segmentation apparatus for an optical character recognition system for segmenting individual character images in an image of a document having many characters prior to performing character identification, including a movable kernel for capturing a sub-image framed within a window having an area corresponding to an area occupied by an individual character, the window being movable in the document image in pixel-by-pixel steps to capture a sub-image for each step of the window, an associative memory for responding to the captured sub-image by producing a corresponding one of a set of images of known characters with which the associative memory has been trained, and a sensor responsive to the behavior of the associative memory for determining whether the sub-image is the image of an individual character or a non-character.
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Citations
32 Claims
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1. Character segmentation apparatus for an optical character recognition system for segmenting individual character images in an image of a document comprising plural characters, prior to performing character identification, said image of a document comprising an array of pixels, said apparatus comprising:
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kernel means for capturing, in said image of a document, a sub-image framed within a window having an area corresponding to an area occupied by an individual character of said document, said window being movable in said image of a document in pixel-by-pixel steps whereby said kernel means captures a sub-image for each step of said window; associative memory means for responding to said sub-image by producing a corresponding one of a set of training images of known characters with which said associative memory has been trained; and sensor means, responsive to said associative memory means producing said corresponding one of a set of training images of known characters, for determining whether said sub-image is the image of an individual character, and segmenting said sub-image as an unidentified individual character image in response to said sub-image corresponding to the image of an individual character. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A character segmentation method in optical character recognition for segmenting individual character images in an image of a document comprising plural characters in preparation for performing character identification, said image of a document comprising an array of pixels, said method comprising:
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capturing, in said image of a document, a sub-image framed within a window having an area corresponding to an area occupied by an individual character of said document, said window being movable in said image of a document in pixel-by-pixel steps whereby a sub-image is captured for each step of said window; responding to said sub-image by producing a corresponding one of a set of training images of known characters; determining from results of said producing step whether said sub-image is the image of an individual character; and in response to said determining step determining that said sub-image is the image of an individual character, segmenting such sub-image as an unidentified individual character image. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. An associative memory with an internal capability of classifying its output as falling into one of a plurality of different sets of training vectors, representative of respective sets of characters and non-characters, with which said associative memory has been trained comprising:
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means for receiving an m×
n element input vector corresponding to an m-by-n input data array;means for producing one of a plurality of training vectors which most closely resembles said input vector, said training vectors each comprising an information portion comprising m×
n elements corresponding to an m-by-n data array and an n element tag portion corresponding to an m+1st row of data not included in said data array, said tag portion being operative to identify said each training vector as a member of a set of training vectors representative of characters or a set of training vectors representative of non-characters. - View Dependent Claims (26, 27, 31, 32)
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28. An associative memory with an internal capability of classifying its output as falling into one of a plurality of classes, comprising:
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means for receiving an input vector; trained neural network means for producing one of a plurality of vectors with which the neural network has been previously trained, which one vector most closely resembles said input vector, by performing an operation which is repeatable until one of said plurality of vectors is produced; and means responsive to the number of times said operation is repeated for determining whether said one vector falls within a predetermined class. - View Dependent Claims (29, 30)
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Specification