HANDWRITTEN NUMERALS RECOGNITION BASED ON SEGMENTED CONTOUR FEATURE
Zhen Lou, Ke Liu · Chinese Journal of Computers · 1999
This paper proposes a new structural method for the recognition of handwritten numerals. Feature cells, which are derived from the primitive segments such as convex arcs, concave arcs, line segments, end point and holes from the contours of numeric characters, are used to describe numeral characters. A method of filtering the curvatures of contour points is developed. A method to measure the similarity between two samples based on the sequences of feature cells is proposed. A two stage recognition methodology is also presented, in which two rejection criteria are introduced. In the first stage of recognition, an input sample is given an identity or categorized as either first class or second class rejection based on similarity measures between the input sample and each of the ten numeral classes. In the second stage of recognition, strategies are adopted to modify the structural description of the input sample if it is in first class rejection and a classifier focussed n pairwise discrimination is applied if the input samples is in second class rejection. Experimental results indicate that the overall performance of the proposed method compares favorably with those achieved by other methods found in the literature.