Baisakhi Sur Phadikar

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Modern technology made storing, sharing, organizing huge amounts of data simple through the Internet of things. Search engines and query-based retrieval databases made access to relevant data easy through ranking and indexing based on content stored. This paper presents a content-based image retrieval technique using image quality assessment (IQA) model.(More)
Most of the methods for video summarisation rely on complicated clustering algorithms that make them too computationally complex for real time applications. This paper presents an efficient approach for video summary generation that does not relay on complex clustering algorithms and does not require frame length as a parameter. The present scheme combines(More)
In this paper, we propose a content-based image retrieval scheme in discrete cosine transform compressed domain with the help of genetic algorithm (GA). A combination of three image features, i.e., color histogram, color moments, and edge histogram, is extracted directly from the compressed domain and is used for similarity matching using the Euclidian(More)
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