CLASSIFICATION TECHNIQUES FOR HANDWRITTEN CHARACTER RECOGNITION

Elastic Matching Techniques for Handwritten Character Recognition

This chapter reviews various elastic matching techniques for handwritten character recognition. Elastic matching is formulated as an optimization problem of planar matching, or pixel-to-pixel correspondence, between two character images under a certain matching model, such as affine and nonlinear. Use of elastic matching instead of rigid matching improves the robustness of recognition systems a...

Optimized segmentation techniques for arabic handwritten numeral character recognition

The segmentation of the Arabic words for recognition still remains a problem to rise for the variability of the writing styles. The adopted technique rests on the hybridization of several segmentation methods based on the various reference levels. The segmentation process led to the decomposition of the writing or words in elementary entities of morphology relatively simple. The choice of primi...

A Survey of Elastic Matching Techniques for Handwritten Character Recognition

This paper presents a survey of elastic matching (EM) techniques employed in handwritten character recognition. EM is often called deformable template, flexible matching, or nonlinear template matching, and defined as the optimization problem of two-dimensional warping (2DW) which specifies the pixel-to-pixel correspondence between two subjected character image patterns. The pattern distance ev...

Transductive Learning for Document Classification and Handwritten Character Recognition

Handwritten Odia Character Recognition

Odia is one of the oldest and popular languages of India, spoken by more than 44 million people, especially in Odisha, India. Some characters in Odia are made up of more than one connected symbols. Compound characters are written by associating modifiers with consonants, resulting in a huge number of possible combinations, running into hundreds of thousands. Therefore, systems developed for rec...