Character recognition with variable subdivisions of a character region

A character recognition method, comprising the steps of:

• providing a binary character image of an unknown character to be identified;
• assigning a plurality of directionality codes to pixels defining a contour of said binary character image selectively according to a predetermined rule to define a code-assigned character image;
• counting a total number of code-assigned pixels;
• forming a pair of first and second projected histograms of the number of code-assigned pixels, said first projected histogram being formed by projecting the code-assigned pixels onto a first predetermined axis and said second projected histogram being formed by projecting the code-assigned pixels onto a second predetermined axis;
• subdiving said code-assigned character image into a plurality of sub-regions based on said total number of code-assigned pixels and said pair of first and second histograms such that each of said sub-regions has a substantially equal number of code-assigned pixels;
• determining a histrogram of said codes for each of said sub-regions to form a collection of histograms of said codes for said input character;
• and
• identifying said input character by comparing said collection of histograms of said codes with each of a plurality of stored collections of histograms of said codes for known characters and selecting one of said known characters, having a highest degree of similarity.

A character recognition method comprising the steps of:

• providing a binary character image of an unknown character to be identified;
• assigning a plurality of directionality codes to pixels defining a contour of said binary character image selectively according to a predetermined rule to define a code-assigned character image;
• counting a total number of code-assigned pixels;
• forming a first projected histogram of the code-assigned pixels, said first projected histogram being formed by projecting the code-assigned pixels onto a first predetermined axis;
• subdiving said code-assigned character image into a plurality of first sections in said first predetermined axis based on said total number of code-assigned pixels and said first projected histogram such that each of said first sections has a substantially equal number of code-assigned pixels;
• subdiving each of said first sections into a plurality of second sections such that each of said second sections has a substantially equal number of code-assigned pixels, thereby subdividing said code-assigned character image into a plurality of sub-regions in the form of mesh;
• determining a histrogram of said codes for each of said sub-regions to form a collection of histograms of said codes for said input character;
• and
• identifying said input character by comparing said collection of histograms of said codes with each of a plurality of stored collections of histograms of said codes for known characters and selecting one of said known characters, having a highest degree of similarity.

A character subdividing method, comprising the steps of:

• providing a binary character image of an input character;
• assigning a plurality of predetermined features to said binary character image selectively in accordance with a predetermined rule, thereby defining a feature-assigned character image;
• counting a total number of assigned features;
• forming a pair of first and second projected histograms of said assigned features, said first projected histogram being formed by projecting said assigned features onto a first predetermined axis and said second projected histogram being formed by projecting said assigned features onto a second predetermined axis;
• and
• subdividing said feature-assigned character image into a plurality of sub-regions based on said total number of said assigned features and said pair of first and second projected histograms such that said sub-regions have substantially equal numbers of said assigned features.

A character subdividing method, comprising the steps of:

• providing a binary character image of an input character;
• assigning a plurality of predetermined features to said binary character image selectively in accordance with a predetermined rule, thereby defining a feature-assigned character image;
• counting a total number of assigned features;
• forming a first projected histogram of said assigned features, said first projected histogram being formed by projecting said assigned features onto a first predetermined axis and said second projected histogram being formed by projecting said assigned features onto a second predetermined axis;
• and
• subdividing said feature-assigned character image into a plurality of first sections in said first predetermined axis based on said total number and said first projected histogram such that said first sections have substantially equal numbers of said assigned features;
• and
• subdividing each of said first sections into a plurality of second sections such that each of said second sections has a substantially equal number of said assigned features, thereby subdividing said feature-assigned character image into a plurality of sub-regions in the form of a mesh.