Offline Handwritten Gurmukhi Character Recognition: A Review

Abstract

All over India more than 12 crore people utilize Gurumukhi script for speaking, documenting & other purposes. A considerable advancement in the work associated with the recognition of handwritten and printed Gurmukhi text has been reported in last few years. From the last few decades offline handwritten character recognition has gained a lot of interest of researchers. It is well known that each individual has some different writing style, so it is very difficult to identify or recognize the handwritten characters. Researchers have worked in this field using various scripts like Hindi, English but a very little work has been done in Gurmukhi script point of view. Based on data acquirement process a concise classification of recognition system has been discussed in this article. Various feature mining techniques & classifiers like power arc fitting ,parabola arc fitting, ,diagonal feature extraction, transition feature extraction, K-NN classifier (Knearest neighbor) & SVM classifier (Support vector machine) are also illustrated in this paper. The methodology for word recognition has also been discussed in this paper.