Character identification plays a vital role in the contemporary world of Image processing. It can solve many composite problems and makes human’s work easier. An instance is Handwritten Character detection. Handwritten recognition is not a novel expertise, but it has not gained community notice until Now. The eventual aim of designing Handwritten Character recognition structure with an accurate...

In this paper, we present a novel method for automatic recognition of isolated Marathi handwritten numerals. Chain code and Fourier Descriptors that capture the information about the shape of the numeral are used as features. After preprocessing the numeral image, the normalized chain code and the Fourier descriptors of the contour of the numeral are extracted. These features are then fed in th...

Slant correction is a preprocessing technique to improve segmentation and recognition accuracy for handwritten word recognition. All conventional slant correction techniques were performed by the estimation of the average slant angle and the shear transformation. In this paper, a nonuniform slant correction technique for handwritten word recognition is proposed where the slant correction proble...

One of the most important and challenging tasks in a handwritten recognition pipeline is the segmentation of handwritten document images into text lines and words. Several problems inherent in handwritten documents such as the difference in the skew angle between text lines or along the same text line, the existence of adjacent text lines or words touching, the existence of characters with diff...

Most online handwriting word recognition (HWR) approaches proceed by segmenting words into isolate characters which are recognized separately. Inspired by results in cognitive psychology, holistic word recognition approaches provides another effective way to deal the problem of HWR. In this paper, we propose a new method for rotation free online unconstrained Chinese word recognition through a ...

We present a simple system that exploits domain knowledge to improve the segmentation and recognition of handwritten ZIP codes. Specifically, we show that the concept of metaclasses of digits, introduced by Morita et al. [16] for recognition of Brazilian bank check dates, can be extended to ZIP code recognition. We also show that, when this domain knowledge is present, integrated segmentation a...

in this paper we address the issue of recognizing farsi handwritten words. two types of gradient features are extracted from a sliding vertical stripe which sweeps across a word image. these are directional and intensity gradient features. the feature vector extracted from each stripe is then coded using the self organizing map (som). in this method each word is modeled using the discrete hidde...

In this paper, combination of zone based symmetric density feature and moment invariant feature is proposed for recognition of isolated handwritten Marathi vowels. Recognition of handwritten Marathi vowels is a challenging task due to their interclass structural similarities. Since a standard database does not exist for handwritten Marathi vowels, as a part of this work database of 2294 handwri...

An examination of how the word recognition system is able to process handwritten words is fundamental to formulate a comprehensive model of visual word recognition. Previous research has revealed that the magnitude of lexical effects (e.g., the word-frequency effect) is greater with handwritten words than with printed words. In the present lexical decision experiments, we examined whether the q...

Handwritten characters recognition (HCR) presents a great challenge in the field of image processing and pattern recognition. This paper presents handwritten English characters recognised using shape based zoning features with the help of neural network (NN) as a classifier. The neural network used is pattern-net. The recognition rate is observed almost 96%. .