Handwritten digit recognition (HDR) shows a significant application in the area of information processing. However, correct such characters from images is complicated task due to immense variations writing style people. Moreover, occurrence several image artifacts like existence intensity variations, blurring, and noise complicates this process. In proposed method, we have tried overcome aforem...

Handwritten character recognition is one of the difficult tasks of pattern recognition due to diverse writing styles. The problem becomes more severe if the characters are written in a cursive fashion with varying orientations. Also there may exist printed characters of different shapes/fonts and sizes in a document image. In the current work, we have presented a novel convex hull based alignme...

This paper describes a technique for the recognition of off-line handwritten Arabic (Indian) numerals using Radon-Fourier-based features. A two stage classification scheme is used. The Nearest Mean (NMC), K-Nearest Neighbor (K-NNC), and Hidden Markov Models (HMMC) Classifiers are used in the first stage and a Structural Classifier (SC) is used in the second stage. A database of 44 writers with ...

The recognition of handwritten digits is an application which has been used as a benchmark for comparing shape recognition methods. We train COSFIRE filters to be selective for different parts of handwritten digits. In analogy with the neurophysiological concept of population coding we use the responses of multiple COSFIRE filters as a shape descriptor of a handwritten digit. We demonstrate the...