A Collaborative approach for segmentation of probe image for efficient texture recognition

Image processing methodologies and domain is quite wide and really efficient now days for real time applications Our work primarily deals with the domain of image segmentation and using segmentation concept texture recognition has been performed with comparative results and simulations performed over a particular image dataset The initial work in our proposed work is to perform segmentation on each part image then performing extraction We have focused on segmentation followed by extraction so that the classification result may not contain much error The conventional approach has been implemented in this regard first and then the main problem that has been formulated is patch up data pixels together which provide error in getting right and appropriate texture In order to deal with the problem formulated in the existing work we have proposed a new commuted method in which the extraction and segmentation of image depends on the dynamic threshold set by use

Hand Written Odia Character Recognition

The world is fast moving towards digitalization. In the age of super-fast computational capabilities, everything has to be made digitalized so as to make the computer understand and thereby process the given information. Optical character recognition is a method by which the computer is made to learn, understand and interpret the languages used and written by the human beings. It provides us a whole new way by which computer can interact with human beings, in their own languages. Hence OCR has been a topic of interest for researchers all around the globe in the past decade and research paper involving OCR is increasing day by day. It is seen that efficient algorithms have increased the speed and accuracy of character recognition. A substantial amount of work has been done on foreign languages such as English , Chinese etc. but very few paper are there for Indian languages baring a few for Hindi and Bengali. Hence our research work was directed towards development of a novel algorithm for Odia character recognition. Odia is one of the eighteen languages recognized by the Indian constituency. It is also one of the oldest languages and is spoken by more than 44 million people in the state of Odisha. Recognition of this particular language is difficult because of a number of similar looking characters and the presence of complex characters. A novel technique is proposed and implemented for the feature extraction method where by a set of 81 feature vectors are extracted to uniquely identify a particular character. The recognition is based on finding the minimum error by implementing the Euclidean distance method. After the implementation of the above technique, accuracy was found to be about 70 % which is much better than many techniques earlier available

Hand-written character recognition using artificial neural network

In todays’ world advancement in sophisticated scientific techniques is pushing further the limits of human outreach in various fields of technology. One such field is the field of character recognition commonly known as OCR (Optical Character Recognition). In this fast paced world there is an immense urge for the digitalisation of printed documents and documentation of information directly in digital form. And there is still some gap in this area even today. OCR techniques and their continuous improvisation from time to time is trying to fill this gap. This project is about devising an algorithm for recognition of hand written characters leaving aside types of OCR that deals with recognition of computer or typewriter printed characters. A novel technique is proposed using Artificial Neural Network including the schemes of feature extraction of the characters and implemented. The persistency in recognition of characters by the AN network was found to be more than 90% of times