International Journal of Advanced Networking and Applications

R. Indra Gandhi ¹, K. P. Kaliyamurthie ¹

Affiliations
1 Department of Computer Science and Engineering, Bharath University, Chennai, Tamil Nadu, IN

Abstract

In the recent trend steganography plays an important role in providing secrecy in internet. Steganography works by replacing bits of useless or unused data in regular computer files with bits of different, invisible information. Cryptography is used to scramble the information sent and make it as a scrambled text which is not understandable. Steganography is used to hide the information so that secrecy can be established. If Steganography and Cryptography are used together it has more advantage for providing security for the information. In this paper hiding of data in digital images formation carried out using adaptive hiding with the optimum pixel adjustment (OPA) algorithm. Resultant system evidences remarkable hiding rates with other Steganographic systems.

Keywords

Data Hiding, IWT, OPA, PSNR, Secret Key, Steganography.

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R. Indra Gandhi ¹, K. Iyakutti ²

Affiliations
1 Department of Computer Science, Mother Teresa Women’s University, Kodaikanal-624102, TN, IN
2 School of Physics, Madurai Kamaraj University, Madurai-62502, TN, IN

Abstract

This paper presents a new approach of Kohonen neural network based Self Organizing Map (SOM) algorithm for Tamil Character Recognition. Which provides much higher performance than the traditional neural network. Approaches: Step 1:It describes how a system is used to recognize a hand written Tamil characters using a classification approach. The aim of the pre-classification is to reduce the number of possible candidates of unknown character, to a subset of the total character set. This is otherwise known as cluster, so the algorithm will try to group similar characters together. Step 2:Members of pre-classified group are further analyzed using a statistical classifier for final recognition. A recognition rate of around 79.9% was achieved for the first choice and more than 98.5% for the top three choices. The result shows that the proposed Kohonen SOM algorithm yields promising output and feasible with other existing techniques.

Keywords

Handwritten Character, SOM, Baseline, Statistical, Structural, Crux, Meticulous and Sobel Edge Detection.

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