In this paper, a modification of PVD (Pixel value differencing) algorithm is used for Image Steganography in spatial domain. It is normalizing secret data value by encoding method to make the new pixel edge difference less among three neighbors (horizontal, vertical and diagonal) and embedding data only to less intensity pixel difference areas or regions. The proposed algorithm shows a good improvemernt for both color and gray-scale images compared to other algorithms. Color images performance are better than gray images. However, in this work the focus is mainly on gray images. The strenght of this scheme is that any random hidden/secret data do not make any shuttle differences to Steg-image compared to original image. The bit plane slicing is used to analyze the maximum payload that has been embeded into the cover image securely. The simulation results show that the proposed algorithm is performing better and showing great consistent results for PSNR, MSE values of any images, also against Steganalysis attack.

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In this paper, an algorithm is developed in 3D Stereo vision to improve image stabilization process for multi-camera viewpoints. Finding accurate unique matching key-points using Harris Laplace corner detection method for different photometric changes and geometric transformation in images. Then improved the connectivity of correct matching pairs by minimizing the global error using spanning tree algorithm. Tree algorithm helps to stabilize randomly positioned camera viewpoints in linear order. The unique matching key-points will be calculated only once with our method. Then calculated planar transformation will be applied for real time video rendering. The proposed algorithm can process more than 200 camera viewpoints within two seconds.

Improving voice quality over wireless communication becomes a demanding feature for social media apps like facebook, whatsapp and other communication channels. Voice-over-internet protocol (VoIP) helps us to make quick telephone calls over the internet. It includes various mechanism which are signaling, controlling and transport layer. Over wireless links, packet loss and high transmission delay damage voice quality. Here VoIP quality will be measured by three main elements which are signaling protocol, audio codec and transport layer. To improve the overall voice quality, we need to combine these three elements properly to get the best score. Otherwise perceptual speech quality will not be the right tool to measure the voice quality. Here we will use Mean Opinion Score (MOS) for calculated jitter values and end to end delay. At the end, best combination of audio codec signaling protocol produced the quality speech.

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