scholarly journals Handwritten Character Recognition Systems Using Image-Fusion and Fuzzy Logic

Author(s):  
Rupsa Chakraborty ◽  
Jaya Sil
Author(s):  
Seiichi Uchida

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 against geometric deformations in handwritten character images. In addition, the optimized matching represents the deformation of handwritten characters and thus is useful for statistical analysis of the deformation. This chapter argues the general property of elastic matching techniques and their classification by matching models and optimization strategies. It also argues various topics and future work related to elastic matching for emphasizing theoretical and practical importance of elastic matching.


2011 ◽  
Vol 20 (03) ◽  
pp. 425-455 ◽  
Author(s):  
RUKSHAN BATUWITA ◽  
VASILE PALADE ◽  
DHARMAPRIYA C. BANDARA

Automated offline handwritten character recognition involves the development of computational methods that can generate descriptions of the handwritten objects from scanned digital images. This is a challenging computational task, due to the vast impreciseness associated with the handwritten patterns of different individuals. Therefore, to be successful, any solution should employ techniques that can effectively handle this imprecise knowledge. Fuzzy Logic, with its ability to deal with the impreciseness arisen due to lack of knowledge, could be successfully used to develop automated systems for handwritten character recognition. This paper presents an approach towards the development of a customizable fuzzy system for offline handwritten character recognition.


Sign in / Sign up

Export Citation Format

Share Document