Author(s)

Kathirvalavakumar Thangairulappan, Palaniappan Rathinasamy

Department of Computer Science, V. H. N. S. N. College, Virudhunagar, India.

A method has been proposed to classify handwritten Arabic numerals in its compressed form using partitioning approach, Leader algorithm and Neural network. Handwritten numerals are represented in a matrix form. Compressing the matrix representation by merging adjacent pair of rows using logical OR operation reduces its size in half. Considering each row as a partitioned portion, clusters are formed for same partition of same digit separately. Leaders of clusters of partitions are used to recognize the patterns by Divide and Conquer approach using proposed ensemble neural network. Experimental results show that the proposed method recognize the patterns accurately.

Handwritten Numerals, Divide and Conquer, Cluster, Leader Algorithm, Neural Network, Ensemble, Classification

Thangairulappan, K. and Rathinasamy, P. (2016) Ensemble Neural Network in Classifying Handwritten Arabic Numerals. Journal of Intelligent Learning Systems and Applications, 8, 1-8. doi: 10.4236/jilsa.2016.81001.