I. V. Muralikrishna

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In digital image classification the conventional statistical approaches for image classification use only the gray values. Different advanced techniques in image classification like Artificial Neural Networks (ANN), Support Vector Machines (SVM), Fuzzy measures, Genetic Algorithms (GA), Fuzzy support Vector Machines (FSVM) and Genetic Algorithms with Neural(More)
In these days Biometric based personnel authentication is evolving as robust method for security. A Palm print is one such reliable biometric entity showcasing all discriminating features. Reducing computational overhead is a challenge in palm print based biometric authentication system. In this paper we examined a new method for preliminary classification(More)
This paper presents VLSI implementation of handwritten digit recognition system based on analog neural network. The recognition system is based on the least hamming distance neural network which both learning and classification. The circuit is simulated using SPICE tool at 180nm CMOS technology. The proposed circuit is modified version of existing circuit(More)
In remote sensing, the satellite images acquired form sensors exhibit either good spectral characteristics (multispectral data) or high spatial characteristics (panchromatic data). Image fusion is required to increase the interpretation quality of images. In this paper an attempt is made to obtain the objective measurements using content based segmentation(More)
Palm print is a widely accepted biometric trait for authentication due to clarity in discriminating the features of palm such as large distance among non-class samples as well as minimum distance between intra-class samples. Area beneath the finger and enclosed by heart line is called as tri-radiated region or inter-distal region. This specific area of palm(More)
Biometric based authentication for secured access to resources has gained importance, due to their reliable, invariant and discriminating features. Palmprint is one such biometric entity. Prior to classification and identification registering a sample palmprint is an important activity. In this paper we propose a computationally effective method for(More)
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