In this paper, an attempt is made to develop off-line recognition strategies for the isolated Handwritten English character(A to Z) and (0 to 9). Challenges in handwritten character recognition wholly lie in the variation and distortion of handwritten characters, since different people may use different style of handwritten, and direction to draw the same shape of the characters of their known ...

In this paper, we present a methodology for off-line Isolated handwritten Devanagari character recognition. The proposed methodology relies on a three feature extraction techniques. The first technique is based on recursive subdivisions of the character image so that the resulting sub-images at each iteration have balanced (approximately equal) numbers of foreground pixels, as far as this is po...

In this study, we introduce a new set of one-dimensional discrete, constant length features to represent two dimensional shape information for HMM (Hidden Markov Model), based handwritten optical character recognition problem. The proposed feature set embeds the two dimensional information into a sequence of onedimensional codes, selected @om a code book. It provides a consistent normalization ...

Hidden Markov Models constitute an established approach often employed for offline handwritten character recognition in digitized documents. The current work aims at evaluating a number of procedures frequently used to define features in the character recognition literature, within a common Hidden Markov Model framework. By separating model and feature structure, this should give a more clear i...

The development of handwriting character recognition (HCR) is an interesting area in pattern recognition. HCR is the ability of a computer to receive and interpret intelligible handwritten input such as digital cameras and other devices. HCR system consists of a number of stages which are preprocessing, feature extraction, classification and followed by the actual recognition. Handwritten can b...

This paper is proposing tlie method for Thai handwritten character recognition. The methods are Robust C-Prototype and Bacl-c-Propagation Neural Network. The objective of experimental is recognition on Thai handwritten character. This is the result of both methods to be appearing accuracy more than 85%.

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...

In this paper a scheme for offline Handwritten Devnagari Character Recognition is proposed, which uses different feature extraction methodologies and recognition algorithms. The proposed system assumes no constraints in writing style or size. First the character is preprocessed and features namely : Chain code histogram and moment invariant features are extracted and fed to Multilayer Perceptro...