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Hadamard based Video Key Frame Extraction using Thepade's Transform Error Vector Rotation with Assorted Similarity Measures

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 122 - Number 5
Year of Publication: 2015
Authors:
Pritam H. Patil
Sudeep D. Thepade
Babita Sonare
10.5120/21699-4810

Pritam H Patil, Sudeep D Thepade and Babita Sonare. Article: Hadamard based Video Key Frame Extraction using Thepade's Transform Error Vector Rotation with Assorted Similarity Measures. International Journal of Computer Applications 122(5):36-40, July 2015. Full text available. BibTeX

@article{key:article,
	author = {Pritam H. Patil and Sudeep D. Thepade and Babita Sonare},
	title = {Article: Hadamard based Video Key Frame Extraction using Thepade's Transform Error Vector Rotation with Assorted Similarity Measures},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {122},
	number = {5},
	pages = {36-40},
	month = {July},
	note = {Full text available}
}

Abstract

In Video summarization is a method to reduce redundancy and generate succinct representation of the video data. In video summarization process, several frames containing similar information need to get processed, this leads to slower processing speed and higher complexity, consuming. More time Video summarization using key frames can ease the speed up of video processing. One of the mechanisms to generate video summaries is to extract key frames which represent the most important content of the video by identifying neard duplicate frames in video. In this paper, novel key frames extraction method is proposed with Thepade's Walsh Hademard Error Vector Rotation (THdEVR) with ten different codebook sizes and and assorted similarity measures. Experimentation done with help of the test bed of videos has shown that higher codebook sizes give better completeness in key frame extraction for video summarization. Experimental results are discussed for video content summarization with five assorted similarity measures like Euclidean Distance, Canberra Distance, Square-Chord Distance, Mean Square Error, Sorensen Distance with proposed THadVR.

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