An algorithm for handwritten digit recognition using projection histograms and SVM classifier

Higher level of image processing usually contains some kind of recognition. Digit recognition is common in applications and handwritten digit recognition is an important subfield. Handwritten digits are characterized by large variations so template matching, in general, is not very efficient. In this paper we describe an algorithm for handwritten digit recognition based on projections histograms. Classification is facilitated by carefully tuned 45 support vector machines (SVM) using One Against One strategy. Our proposed algorithm was tested on standard benchmark images from MNIST database and it achieved remarkable global accuracy of 99.05%, with possibilities for further improvement.