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Research Paper | Computer Science & Engineering | India | Volume 5 Issue 2, February 2016

Performance Comparison of Devanagari and Gurmukhi Handwritten Numerals Recognition

Gita Sinha ^[3] | Rakesh Kumar Roshan

Abstract: In this paper we proposed two different methods for Numeral Recognition are and compared their performance. The objective of this paper is to provide an efficient and reliable method for recognition of handwritten numerals. First method employs Image Centroid Zone feature extraction and recognition algorithm. In this method the features of the image are extracted and these feature set is then compared with the feature set of database image for classification. While second method contains Zone Centroid Zone algorithms for feature extraction and the features are applied to support vector machine [SVM] for recognition of input image. Handwritten Optical Numeral recognition [HONR] is important research area because of its wide applications in many areas like Cheque Reading in Bank, postcode reading, form processing, Post office, Hospitals, signature verification etc.

Keywords: Handwritten Numeral Recognition, Grid Technique, ANN, Feature Extraction, Classification

Edition: Volume 5 Issue 2, February 2016,

Pages: 310 - 316