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Articles by V. Kavitha
Total Records ( 3 ) for V. Kavitha
  A. Anasuya Threse Innocent , V. Kavitha and K.S. Easwarakumar
  The increasing network transaction of sensitive information needs an efficient and secured way of information transmission. In today’s era of Information Technology, there is a strong need for transmitting heavy volumes of information within the available bandwidth. This can be achieved by means of compression techniques thereby the efficiency of data transmission is increased. Data security has to be incorporated for secure transaction of sensitive data. Cryptographic technique ensures privacy by keeping the information hidden from anyone to whom it is not intended. The present scenario does encryption and compression as individual process to achieve secure and effective transmission. Pre-analysis proves that performing compression and then encryption is the best. To overcome the individual compression and encryption process and to minimize the time of execution, this trigonometry approach does simultaneous compression and encryption.
  A. Merry Ida , V. Kavitha and K.S. Easwarakumar
  In e-commerce applications Authentication is provided with the combination of user id and password that results in fraud and misuse. Automated biometrics technology in general and fingerprints in particular, provide an accurate and reliable authentication method. However, fingerprint based authentication requires accessing fingerprint images scanned remotely at the user`s workstation, a potentially weak point in the security system. Even though the communication channel is encrypted, stored or synthetic fingerprint images might be fraudulently transmitted. To enhance security, embedding additional information directly in compressed fingerprint images can use data hiding technique. Integrity is incorporated while transmitting fingerprint for authentication. Data Integrity is achieved by hashing the features of fingerprint to that of Unique Person Identification (UPID).
  M. Manju and V. Kavitha
  In this study, the accuracy of finger print recognition problem is been addressed. As per the literature the Back Propagation Network (BPN) for fingerprint recognition has resulted in inconsistent with unpredictable performance. This research has proposed the soft computing tool to images to overcome the low recognition rate and the low accuracy in fingerprint identification. Fuzzy logic is worn to eliminate the false minutiae from the fingerprint. Genetic algorithm has been incorporated to optimize the weights of neural network and the accuracy in the recognition process has been improved. The proposed method is implemented on the FVC 2004 DB1 database. The Laplacian based Pyramidal Model has strongly supported in fingerprint enhancement process which has increased the Peak Signal to Noise Ratio (PSNR) and decreased the Mean Square Error (MSE). The results have proven that the false minutiae have been eliminated by applying fuzzy rules and also the Equal Error Rate (EER) has been reduced. The increase in the recognition accuracy moreover in turn has reduced the training and the testing time.
 
 
 
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