R. G. Benne

Learn More
In this paper, a novel approach for Kannada, Telugu and Devanagari handwritten numerals recognition based on global and local structural features is proposed. Probabilistic Neural Network (PNN) Classifier is used to classify the Kannada, Telugu and Devanagari numerals separately. Algorithm is validated with Kannada, Telugu and Devanagari numerals dataset by(More)
In this paper a fast and novel method is proposed for multi-font multi-size Kannada numeral recognition which is thinning free and without size normalization approach. The different structural feature are used for numeral recognition namely, directional density of pixels in four directions, water reservoirs, maximum profile distances, and fill hole density(More)
In this paper a script independent automatic numeral recognition system is proposed. A single algorithm is proposed for recognition of Kannada, Telugu and Devanagari handwritten numerals. In general the number of classes for numeral recognition system for a scripts/language is 10. Here, three scripts are considered for numeral recognition forming 30(More)
In this paper a novel approach is proposed based on single Euler number feature which is free from thinning and size normalization for multi-font and multi-size Kannada numeral recognition system. A nearest neighbor classification is used for classification of Kannada numerals by considering the Euclidian distance. A total 1500 numeral images with different(More)
  • 1