Title – Self-Mutation of Hybrid Wavelet Transform with Cosine-Kekre, Cosine-Haar, Cosine-Walsh, Walsh-Cosine, Haar-Cosine and Kekre-Cosine for Content Based Video Retrieval
Author(s) – Nalini Yadav, Sudeep D. Thepade
Country – India
Abstract – Efficient access of multimedia data is a big requirement of current decade. With advancement of storage and network technologies, there is huge generation of multimedia data. To store and access this multimedia data efficiently and accurately is a challenge. Videos are part of multimedia data. Important activities in video retrieval are efficient storage and accurate retrieval of relevant videos. This paper proposes a novel Content based Video Retrieval method using energy contents of the video. Proposed energy contents extraction method includes self-mutation of Hybrid Wavelet Transform. Further in proposed approach the efficient method to reduce the feature vector size using partial energies of the video content is also enlightened. Paper also list downs the performance comparison of four similarity measures alias Euclidean Distance, City Block Metric, Sorensen Distance, Kulczynski Distance. This paper aims at using a novel method for generation of orthogonal transform called Self Mutation of Hybrid Wavelet Transform and judging the efficiency of same for Content Based Video Retrieval with energy compaction using partial energies.
Keywords – Self Mutation; Hybrid Wavelet Transform; Energy Compaction; Similarity measures; Partial Energy; Cosine Transform; Haar Transform; Walsh Transform
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