In this paper, a pristine method of tough digital video watermarking algorithm in H.264 compressed domain is articulated. Most of the video watermarking techniques interleave the watermark in Iframes but in this paper a fabulous method of blind low complexity video watermarking in P-frames for H.264 video is proposed. Our algorithm decides which 4x4 block within the macro-block of P-frame will be set in based on the covert key. The proposed method restricts embedding by selecting only the nonzero quantized ACresiduals of P-frames, thus escalating the watermark robustness. Simulation outcome illustrate that there is decrease in bit rate and at the same time it is robust to quite a few diverse attacks. Keywords-Digital video watermarking, AC Coefficient, P-frame, bit rate, H.264.

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In the medical field accurate diagnosis is very crucial for successful treatment. With the rapid development of technology, the ever increasing quantity of medical images is produced in hospitals for diagnosing. Content-Based Image Retrieval (CBMIR) is a technique retrieves similar medical images from large database using visual features such as color, texture and shape. This paper focuses a novel method to increase the performance of Content Based Medical Image Retrieval System (CBMIRS). A multiple features vector gives betterquality performance as compared to a single feature. This paper presents a new approach which takes the advantages of each individual feature. The content of the image extracted with the help of texture and region based shape descriptor, which have better features representation capabilities and are more robust to noise. The texture features are extracted with the help of Gabor filter and chebichef Moments used for Shape features extraction. The similar medical images will be retrieved by comparing the feature vector of the query image with the corresponding feature vectors of the data base images using Euclidian distance as a similarity measure. Experimental results show that proposed method achieves highest retrieval performance in comparison with individual feature based retrieval system.

an effective content-based image retrieval system is essential to locate required medical images in huge databases. This paper proposes an effective approach to improve the effectiveness of retrieval system. The proposed scheme involves first, by detecting the boundary of the image, based on intensity gradient vector image model followed by exploring the content of the interior boundary with the help of multiple features using Gabor feature, Local line binary pattern and moment based features .The Euclidean distance are used for similarity measure and then these distances are sorted out and ranked. As a result, the Recall rate enormously improved and Error rate has been decreased when compared to the existing retrieval systems.