Pattern recognition method

A pattern recognition method comprising the steps of:

• detecting a change in type between two consecutive pixels in a direction of a raster-scan which is carried out for a binary image of an unknown pattern, one of said two consecutive pixels being designated as a start point from which trace of a contour of said binary image starts;
• tracing said contour of said binary image in a predetermined direction along a predetermined type of pixels in such a way that four adjacent pixels on upper, lower, left-hand and right-hand sides of a point of interest are checked in a predetermined rotational direction starting from one pixel out of said four adjacent pixels which is positioned on a predetermined side at an angle of 90.degree. with respect to a moving direction in which the trace proceeded towards said point of interest and that one pixel of a predeterminted type out of said four adjacent pixels which is first found by said check is designated as a next trace point following said point of interest;
• extracting a feature of each of the pixels at the traced points which form an image of said contour of said pattern, said feature being a directional code which indicates a moving direction from said point of interest to said next trace point;
• and
• identifying said unknown pattern by comparing said features of said unknown pattern with features of a known pattern.

A pattern recognition method comprising the steps of:

• tracing a contour of a binary image of an unknown pattern which is obtained by a raster-scan;
• extracting a feature of each of pixels at said contour which form an image of said contour of said unknown pattern;
• registering said feature of each of pixels in a memory region in order of appearance of said feature, so that a one-dimensional code sequence is registered in said memory region;
• dividing said memory region which stores said one-dimensional code sequence into a plurality of one-dimensional sub-regions, each including a plurality of partial code sequences;
• calculating a feature quantity for each of sub-regions;
• and
• identifying said unknown pattern by comparing said feature quantity for each sub-region of said unknown pattern with a feature quantity for each respective sub-region of a known pattern.