Neha Satam

MM
3papers
58citations
Novelty28%
AI Score18

3 Papers

MMNov 7, 2013
Image Steganography using Karhunen-Loeve Transform and Least Bit Substitution

Ankit Chadha, Neha Satam, Rakshak Sood et al.

As communication channels are increasing in number, reliability of faithful communication is reducing. Hacking and tempering of data are two major issues for which security should be provided by channel. This raises the importance of steganography. In this paper, a novel method to encode the message information inside a carrier image has been described. It uses Karhunen-Loève Transform for compression of data and Least Bit Substitution for data encryption. Compression removes redundancy and thus also provides encoding to a level. It is taken further by means of Least Bit Substitution. The algorithm used for this purpose uses pixel matrix which serves as a best tool to work on. Three different sets of images were used with three different numbers of bits to be substituted by message information. The experimental results show that algorithm is time efficient and provides high data capacity. Further, it can decrypt the original data effectively. Parameters such as carrier error and message error were calculated for each set and were compared for performance analysis.

CVNov 7, 2013
Biometric Signature Processing & Recognition Using Radial Basis Function Network

Ankit Chadha, Neha Satam, Vibha Wali

Automatic recognition of signature is a challenging problem which has received much attention during recent years due to its many applications in different fields. Signature has been used for long time for verification and authentication purpose. Earlier methods were manual but nowadays they are getting digitized. This paper provides an efficient method to signature recognition using Radial Basis Function Network. The network is trained with sample images in database. Feature extraction is performed before using them for training. For testing purpose, an image is made to undergo rotation-translation-scaling correction and then given to network. The network successfully identifies the original image and gives correct output for stored database images also. The method provides recognition rate of approximately 80% for 200 samples.

MMSep 26, 2013
An Efficient Method for Image and Audio Steganography using Least Significant Bit (LSB) Substitution

Ankit Chadha, Neha Satam

In order to improve the data hiding in all types of multimedia data formats such as image and audio and to make hidden message imperceptible, a novel method for steganography is introduced in this paper. It is based on Least Significant Bit (LSB) manipulation and inclusion of redundant noise as secret key in the message. This method is applied to data hiding in images. For data hiding in audio, Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) both are used. All the results displayed prove to be time-efficient and effective. Also the algorithm is tested for various numbers of bits. For those values of bits, Mean Square Error (MSE) and Peak-Signal-to-Noise-Ratio (PSNR) are calculated and plotted. Experimental results show that the stego-image is visually indistinguishable from the original cover-image when n<=4, because of better PSNR which is achieved by this technique. The final results obtained after steganography process does not reveal presence of any hidden message, thus qualifying the criteria of imperceptible message.