Handwritten Text Recognition

This text recognition lays emphasis on technique to recognize handwritten English characters using MATLAB. Here a novel solution is proposed for performing English character recognition. Handwritten character can be converted into the text. It may be either scanned document or paint image. Here the application is alphabetic letters are assigned with numerals accordingly. The new venture in this topic is to make off-line handwritten text recognition more accurate & challengeable. Here what is uploaded will come in the form of original text. Pursued by the preprocessing technique, feature extraction and recognition. The approach can be utilized in MATLAB for recognizing off-line handwritten English characters. Index Terms — text recognition, handwritten, MATLAB INTRODUCTION Recognition is regarded as a basic attribute of human beings, as well as other living organisms. A pattern is the description of an object. Performing the acts of recognition in every walk of our lives, such as recognition of objects around us, recognizing a friend in a crowd, recognizing voice of a known individual and recognizing handwritten characters. According to the nature of the patterns to be recognized, we may divide our acts of recognition into two major types, namely, the recognition of concrete items and the recognition of abstract items. The concrete items of recognition include spatial patterns like characters, finger prints, weather maps, objects etc and temporal patterns like speech waveforms, electrocardiograms, target signatures, and time series Tou et al (1974). An example of recognition of an abstract item is the recognition of solution to a problem when your eyes and ears are closed. However we are concerned only with recognition of concrete items. Recognition of concrete patterns by human beings may be considered as a physiological problem which involves a relationship between a person and a physical stimulus. When a person perceives a pattern, he makes an inductive inference and associates this perception with some general concepts or clues which he has derived from his past experience. Human recognition in reality is a question of estimating the relative odds that the input data can be associated with one of a set of known statistical populations which depend on our past experience and which form the clues and the a priori information for recognition. Thus, the problem of pattern recognition may be regarded as one of discriminating the input data not between individual patterns but between populations, via the search for features or invariant attributes among members of a population. Hence, Pattern Recognition can be defined as the classification of input data into identifiable classes via the extraction of significant features or attributes of the data from a background of irrelevant details. A Character recognition system is a pattern recognition system which receives scanned preprocessed data as input and identifies the name of the character by comparing it with the prototype characters already in the memory by Annadurai et al (2007). The study of pattern recognition problems may be logically divided into two major categories Ullman (1982). The study of the pattern recognition capability of human beings and other living organisms. In this paper, the impart main emphasis on word recognition & hence assume that the handwritten texts are already segmented into words segment. Characters are limited to be digits on account of time constraints. Since it requires less image processing & data collection efforts. These handwritten texts are varied. Using the lexicon text is taken out the possibility towards correcting recognition. I. LITERATURE REVIEW The Literature study is in category namely research work in character recognition. Since 1980 a large amount of work has been carried out in character recognition. In the early 80's most of the works are related to either printed word or handwritten characters recognition only. In the mid of 80's Nagy et al (1987) demonstrated a heuristic algorithm for assigning alphabetic identity for symbols in a textual context, and a rule based contextual post processor for Devanagari recognition was suggested by Sinha (1985). Much of the work upto 1987 has been reported in Govindan's thesis (1988). The following are some of the recent works in this area. Kahan et al (1987) described the state of the system (OCR during 1987) that recognizes printed text of various fonts and sizes to any extent. Cheng et al (1985) discussed a method based on the concept of fuzzy set for handwritten Chinese character recognition. The strokes of the characters and its type and location features are concentrated to recognize the characters using fuzzy entropy. The state-of-the-art of Methodology and algorithms of fuzzy sets for real world use of Fuzzy sets in Pattern Recognition is described by Pedrycz (1990). The recognition and classification are provided with examples. Recognition of handwritten and machine printed text for postal address interpretation using various algorithms are discussed by Srihari (1992, 1993). Current state-of-the-art of new generation of handwriting recognition system with lessons learned and M.Sivasankari et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (3) , 2014, 3608-3610