Method and apparatus for handwritten character recognition

Claim 1

A method for extracting features of a written character, comprising: raster scanning said written character to determine stroke-based features, including contour profiles; extracting vertical strokes of said character; and extracting horizontal strokes of said character, wherein said stroke-based features include a run length segment distribution spectrum which is used to estimate the character stroke width.

Claim 2

A method for extracting features of a written character, comprising: raster scanning said written character to determine stroke-based features, including contour profiles; extracting vertical strokes of said character; and extracting horizontal strokes of said character, wherein said stroke-based features include a run length segment distribution spectrum which is used to estimate the character stroke width.

Claim 3

A method for extracting features of a written character, comprising: raster scanning said written character to determine stroke-based features, including contour profiles; extracting vertical strokes of said character; and extracting horizontal strokes of said character, wherein said stroke-based features include a run length segment distribution spectrum which is used to estimate the character stroke width and also include a number of run length segments per horizontal scanning row.

Claim 4

A method for extracting features of a written character, comprising: raster scanning said written character to determine stroke-based features, including contour profiles; extracting vertical strokes of said character; and extracting horizontal strokes of said character, wherein said stroke-based features include a run length segment distribution spectrum which is used to estimate the character stroke width and also include a number of run length segments per horizontal scanning row.

Claim 5

A method for written character recognition, comprising: thresholding an input gray level character to derive its bilevel image; making a first-pass raster scan of said bilevel image and extracting stroke-based features of said image including a run length distribution spectrum which is used to estimate a stroke width of said character; making a second-pass raster scan of said bilevel image and extracting vertical strokes of said image, where vertical strokes are defined as adjacent segments of the bilevel image that have stroke widths within the estimated stroke width and have approximately vertical collinear centers, and classifying any remaining components of the bilevel image as horizontal strokes which are segments which include true horizontal segments as well as segments having angular orientations; classifying said extracted features and vertical and horizontal strokes based upon a set of predetermined rules; determining the identity of said character utilizing said classification; and indicating the identity of said character.

Claim 6

A method for written character recognition, comprising: thresholding an input gray level character to derive its bilevel image; making a first-pass raster scan of said bilevel image and extracting stroke-based features of said image including a run length distribution spectrum which is used to estimate a stroke width of said character; making a second-pass raster scan of said bilevel image and extracting vertical strokes of said image, where vertical strokes are defined as adjacent segments of the bilevel image that have stroke widths within the estimated stroke width and have approximately vertical collinear centers, and classifying any remaining components of the bilevel image as horizontal strokes which are segments which include true horizontal segments as well as segments having angular orientations; classifying said extracted features and vertical and horizontal strokes based upon a set of predetermined rules; determining the identity of said character utilizing said classification; and indicating the identity of said character.

Claim 7

A method for written character recognition, comprising: thresholding an input gray level character to derive its bilevel image; making a first-pass raster scan of said bilevel image and extracting stroke-based features of said image, including separate right and left contour profiles, horizontal projection profile, run length distribution spectrum which is used to estimate a stroke width of said character, and number of run length segments per horizontal scanning row; making a second-pass raster scan of said bilevel image and extracting vertical strokes of said image, where vertical strokes are defined as adjacent segments of the bilevel image that have stroke widths within the estimated stroke width and have approximately vertical collinear centers, and classifying any remaining components of the bilevel image as horizontal strokes which are segments which include true horizontal segments as well as segments having angular orientations; classifying said extracted features and vertical and horizontal strokes based upon a set of predetermined rules; determining the identity of said character utilizing said classification; and indicating the identity of said character.

Claim 8

A method for written character recognition, comprising: thresholding an input gray level character to derive its bilevel image; making a first-pass raster scan of said bilevel image and extracting stroke-based features of said image, including separate right and left contour profiles, horizontal projection profile, run length distribution spectrum which is used to estimate a stroke width of said character, and number of run length segments per horizontal scanning row; making a second-pass raster scan of said bilevel image and extracting vertical strokes of said image, where vertical strokes are defined as adjacent segments of the bilevel image that have stroke widths within the estimated stroke width and have approximately vertical collinear centers, and classifying any remaining components of the bilevel image as horizontal strokes which are segments which include true horizontal segments as well as segments having angular orientations; classifying said extracted features and vertical and horizontal strokes based upon a set of predetermined rules; determining the identity of said character utilizing said classification; and indicating the identity of said character.