• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.641-644
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• 2015

In this paper, we propose a precise frame-level near-duplicate video matching algorithm. First, a binary frame descriptor for near-duplicate video matching is proposed. The binary frame descriptor divides a frame into patches and represent the relations between patches in bits. Seconds, we formulate a cost function for the matching, composed of matching costs and compensatory costs. Then, we roughly determine initial matchings and refine the matchings iteratively to minimize the cost function. Experimental results demonstrate that the proposed algorithm provides efficient performance for frame-level near duplicate video matching.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.64-73
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• 2012

In this paper, we propose a method to search for identical videos. The proposed method is spatio-temporal group feature fingerprinting. Frame of video is extracted from fixed rate method and is partitioned into vertical group and horizontal group. Descriptor is made of each group feature that is extracted from binary fingerprinting. Next, use descriptor of original video to build a two type of fingerprinting database and matching with query video. To efficient and effective video copy detection, method have high robustness, independence, matching speed. In proposed method, group feature have high robustness and independence in variable modification of video. Building a original fingerprinting database is able to fast matching with query video. The proposed method shows performance improvement in variable modifications in comparison to the existing methods. Especially, very singular performance in speed improvement is great advantage of this paper.