The optical character recognition (OCR) is the process of converting textual scanned image into a computer editable format. The proposed OCR system is for complex handwritten Kannada characters. One of the major challenges faced by Kannada OCR system is recognition of handwritten text from an image. The input text image is subjected to preprocessing and then converted into binary image. Segment...

This paper presents an OCR (optical character recognition) system for the handwritten Gurmukhi characters using different wavelet transforms. There is a lot of research work available in case of optical character recognition of various languages like English, Chinese, and Arabic etc. But in case of handwritten Gurmukhi script very less research has been done. In this paper, Different Wavelet tr...

Handwritten character recognition is always a frontier area of research in the field of pattern recognition. Even though, sufficient studies have performed in foreign scripts like Arabic, Chinese and Japanese, only a very few work can be traced for handwritten character recognition mainly for the south Indian scripts. Multiple combinations of vowels and consonants along with its modifiers led t...

Character recognition comes into play when we want to recognize the hand written characters in a perticular natural language. It can be done using various types of method and algorithm that are already defined.Character recognition is essentially a pattern recognition problem and has been around for years now. Although there are implementation of hand written characters in many natural language...

Computers are greatly influencing the lives of human beings and their usage is increasing at a tremendous rate. The ease with which we can exchange information between user and computer is of immense importance today because input devices such as keyboard and mouse have limitations vis-à-vis input through natural handwriting. We can use the online handwriting recognition process for a quick and...

Problem Statement: Handwriting recognition has attracted voluminous research in recent times. The segmentation and recognition of the characters from handwritten scripts incorporates considerable overhead. Almost all the existing handwritten character recognition techniques use neural network approach, which requires lot of preprocessing and hence accomplishing these problems using neural netwo...

Character segmentation has long been one of the most critical areas of optical character recognition process. Through this operation, an image of a sequence of characters, which may be connected in some cases, is decomposed into sub-images of individual alphabetic symbols. In this paper, segmentation of cursive handwritten script of world’s fourth popular language, Bengali, is considered. Unlik...

An efficient method for increasing the generalization capacity of neural character recognition is presented. The network uses a biologically inspired architecture for feature extraction and character classification. The numerical methods used are, however, optimized for use on massively parallel array processors. The method for training set construction, when applied to handwritten digit recogn...

Support Vector Machines (SVMs) have successfully been used in recognizing printed characters. In the present work, we have used this classification technique to recognize handwritten characters. Recognition of handwritten characters is a difficult task owing to various writing styles of individuals. A scheme for offline handwritten Gurmukhi character recognition based on SVMs is presented in th...

Handwritten character recognition is always a frontier area of research in the field of pattern recognition. There is a large demand for OCR on hand written documents in Image processing. Even though, sufficient studies have performed in foreign scripts like Arabic, Chinese and Japanese, only a very few work can be traced for handwritten character recognition mainly for the south Indian scripts...