J. Jennifer Ranjani

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Secure Content Based Image Retrieval (CBIR) deals with retrieving similar images from an image database without revealing the contents of the query image. In the traditional CBIR, it is not practically possible to store large volumes of image database locally. Hence, image database has to be stored in a remote server. In this paper, the images are encrypted(More)
In this research work a fully automated and given to automatic algorithm to detect Quantification of Kidney Stones by using symmetric analysis, which is proposed in this paper. Here we detect the renal-stones, segment the renal regions and calculate the area of the renal which is occupied by kidney stones. The quantitative analysis of kidney stones allows(More)
— The popular international standard for compression, the Joint Photographers Expert Group (JPEG) can lead to noticeable discontinuities along the boundaries called the 'blocking artifacts'. When the image is JPEG compressed the high frequency details of the coded image are mainly contaminated by quantization noise. The effect of quantization noise in the(More)
Content-based image retrieval (CBIR), also known as query by image content is one of the applications of computer vision. In CBIR, the contents derived from the image like color, shapes, and textures are analyzed rather than the metadata such as keywords, tags, and/or descriptions associated with the image. In this paper, the texture features of the image(More)
Automatic detection of sustained intensity changes (edges) in SAR images for applications requiring localization and identification of objects is complicated by the nature of the speckle. The speckle is characterized by a high degree of correlation and multiplicative signal dependence. Ratio based detectors like MRoA and RGoA edge detector use predefined(More)
In this paper, a novel information hiding scheme based on pseudo magic squares is proposed. The pseudo magic square pattern is generated using the Knight’s move algorithm, whereas diamond encoding (DE) and adaptive pixel pair matching (APPM) embedding schemes adapts rhombic shaped and non-uniform pattern respectively. The momentous feature of the proposed(More)
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