Asmita Deshmukh

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Content-based image retrieval (CBIR) systems demonstrate excellent performance at computing low-level features from pixel representations. Its output does not reflect the overall desire of the user. The systems perform poorly in extracting high-level (semantic) features that include objects and their meanings, actions and feelings. This is, referred to as(More)
The key problem in achieving efficient and user friendly Content Based Image Retrieval (CBIR), in domain of images is the development of a search mechanism to guarantee delivery of minimal irrelevant information (high precision) while insuring that relevant information is not overlooked (high recall). The current CBIR results need to be improved by indexing(More)
The CBIR problem is motivated by the need to search the exponentially increasing space of image and image databases efficiently and effectively. The survey feature extraction and selection techniques adopted in content based image retrieval (CBIR), is a technique that uses the visual content of a still image to search for similar images in large scale image(More)
Content Based Image Retrieval is one of the active research areas. With emerging technologies of multimedia ,communication and processing large volume of image database is used . Current approaches include the use of color, texture and shape information for CBIR. Texture feature is a kind of visual characteristic that does not rely on color and intensity(More)
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