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Proceedings Paper

Ordinal-based method for robust image/video signature generation
Author(s): Daniel Chongli Chen; Lekha Chaisorn; Susanto Rahardja
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Paper Abstract

This paper proposes an algorithm for generating a video signature based on an ordinal measure. Current methods which use a measure of temporal ordinal rank are robust to many transformations but can only detect the entire query video, not a segment of the query, while methods which use local features may be more robust to certain transformations but less robust to excessive noise. The proposed algorithm incorporates region-based spatial information while maintaining a strong robustness to noise, different resolutions, illumination shifts and video file formats. In our method, a frame is first divided into blocks. For each pixel in a block, a slice (a binary image computed based on the comparison between the greyscale intensity of each pixel in the frame and the reference pixel) is generated. The slices of all the pixels in a block are then added component-wise to obtain a metaslice for the block. In order to compute the distance between any two frames, the Euclidean distance between corresponding metaslices of the two frames is computed to obtain the metadistance between two blocks. Summing the metadifferences over all blocks and normalizing give the final measure of distance between the two frames. To improve the speed of the algorithm, keyframes are first downsized and pixel intensity values are represented by the average of a small block. A table of frame differences between two sets of keyframes from two video sequences is constructed and then converted to a similarity matrix using a threshold. The longest chain of consecutive similar keyframes is found and this produces the best matching video sequence between the two videos. This algorithm is capable of taking into account differences between videos at various scales and is useful for finding duplicate or modified copies of a query video in a database. Preliminary experimental results are encouraging and demonstrate the potential of the proposed algorithm.

Paper Details

Date Published: 15 September 2008
PDF: 10 pages
Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70732I (15 September 2008); doi: 10.1117/12.802714
Show Author Affiliations
Daniel Chongli Chen, A*STAR Institute for Infocomm Research (Singapore)
Lekha Chaisorn, A*STAR Institute for Infocomm Research (Singapore)
Susanto Rahardja, A*STAR Institute for Infocomm Research (Singapore)

Published in SPIE Proceedings Vol. 7073:
Applications of Digital Image Processing XXXI
Andrew G. Tescher, Editor(s)

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