Biometrics and Bioinformatics

Abstract

Pattern recognition plays very important role in handwritten capital English letters. It will be covered development in the areas of engineering, artificial intelligence, statistics, computer science, psychology and physiology; image processing etc. from 1960.The goal of pattern recognition is to clarify these complicated mechanisms of decision-making processes and to automate these functions using computers. However, because of the complex Nature of the problem, most pattern recognition research has been concentrated on more realistic problems, such as the recognition of handwritten digits and the classification. Pattern matching and analysis of handwritten (PMAAOH) has been an active area of research and due to its diverse applicable environment; it continues to be a challenging research topic.

Pattern matching and analysis of handwritten (PMAAOH) is a active problem researchers had been research into this area for so long especially in the recent years. In my study there are many fields concern with English capital letters, for example, checks in banks or recognizing numbers in car plates, the subject of recognition appears. A system for recognizing isolated English capital letters will be as an approach for capital English letters with such application Among the different traditional approaches of pattern matching and recognition the statistical approach has been most intensively studied and used in real time practice. More commonly, the addition of artificial neural network techniques significant attention. The design of a handwritten capital English characters recognition system requires definition of pattern classes, sensing environment, pattern representation, feature extraction and selection,  classifier design and learning, selection of training and test samples, and performance evaluation.

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Abstract

A neural network is a machine that is designed to model the way in which the brain performs a particular task or function of interest: The network is usually implemented by using electronic components or is simulated in software on a digital computer. “A neural network is a massively parallel distributed processor made up of simple processing units which has a natural propensity for storing experiential knowledge and making it available for use. It resembles the brain in two respects:

1. Knowledge is required by the network from its environment through a learning process.

2. Interneuron connection strengths, known as synaptic weights, are used to store the acquired knowledge”.

   An important contribution of this research lies in the provision of a much needed different person’s handwritten database. This offers practical benefits for pattern matching and analysis of handwritten digits and providing a facilitate training and testing. In this research work i) 100 persons of handwritten digits from 0 to 9 have been collected. Then on that database MLP Classifier is applied. It is found that the result of MLP classifier is giving only 45.50% of accuracy. Therefore new database has been formed by following Way of writing characters. ii) Once again new collected data passes over pre-processing of MLP. In pre-processing different operations are perform such as image acquisition, gray conversion, binary conversion, edge detection, image dilate and image fill. After completion of pre-processing image passes over for normalization and then to feature extraction. Now lastly passes over classifier Gradient descent back propagation with adaptive learning rate. Finally handwritten digit is recognized by 80.10%.

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