Recognizing handwritten Arabic numerals using partitioning approach and KNN algorithm

Abstract

A method has been proposed to classify handwritten Arabic numerals in its compressed form using partitioning approach and K-Nearest Neighbour (KNN) algorithm. Handwritten numerals are represented in a matrix form. Compressing the matrix representation by merging adjacent pair of rows, by OR-ing the bits in corresponding positions, reduces its size in half. Considering each row as a partitioned portion, clusters are formed for each partition of a digit separately. Leaders of clusters of partitions are used to recognize the patterns by Divide and Conquer approach and KNN algorithm. Experimental results show that the proposed method recognize the patterns accurately.