• Journal of Information Processing Systems
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• v.12 no.3
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• pp.502-510
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• 2016

Considering video copy transform diversity, a multi-feature video copy detection algorithm based on a Speeded-Up Robust Features (SURF) local descriptor is proposed in this paper. Video copy coarse detection is done by an ordinal measure (OM) algorithm after the video is preprocessed. If the matching result is greater than the specified threshold, the video copy fine detection is done based on a SURF descriptor and a box filter is used to extract integral video. In order to improve video copy detection speed, the Hessian matrix trace of the SURF descriptor is used to pre-match, and dimension reduction is done to the traditional SURF feature vector for video matching. Our experimental results indicate that video copy detection precision and recall are greatly improved compared with traditional algorithms, and that our proposed multiple features algorithm has good robustness and discrimination accuracy, as it demonstrated that video detection speed was also improved.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.497-502
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• 2003

Content-based video copy detection is a complementary approach to watermarking. As opposed to watermarking, which relies on inserting a distinct pattern into the video stream, video copy detection techniques match content-based signatures to detect copies of video. Existing typical content-based copy detection schemes have relied on image matching which is based on key frame detection. This paper proposes a motion directional histogram, which is quantized and accumulated the direction of motion, for video copy detection. The video clip is represented by a motion directional histogram as a 1-dimensional graph. This method is suitable for real time indexing and counting the TV CF verification that is high motion video clips.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.96-102
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• 2003

Video copy detection is a complementary approach to watermarking. As opposed to watermarking, which relies on inserting a distinct pattern into the video stream, video copy detection techniques match content-based signatures to detect copies of video. Existing typical content-based copy detection schemes have relied on image matching. This paper proposes two new sequence matching techniques for copy detection and compares the performance with color techniques that is the existing techniques. Motion, intensity and color-based signatures are compared in the context of copy detection. Comparison of experimental results are reported on detecting copies of movie clips.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3520-3537
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• 2014

Video copy detection methods have emerged in recent years for a variety of applications. However, the lack of efficiency in the usual retrieval systems restricts their use. In this paper, we propose a parallel implementation strategy for content based video copy detection (CBCD) by using a multi-core processor. This strategy can support video copy detection effectively, and the processing time tends to decrease linearly as the number of processors increases. Experiments have shown that our approach is successful in speeding up computation and as well as in keeping the performance.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1070-1075
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• 2014

Due to a number of illegal copied videos, many video content markets have been threatened. Since this copied videos have intercepted the profits of the content holders, content developers lose the will to generate new contents. Therefore, video copy detection approaches have been developed to protect the copyrights of video contents. However, many illegal uploader who generate copied videos used video transformations to avoid video copy detection systems. Among of the video transformations, rotation and flipping did not distorted the quality of video contents. Thus, these two video transformations were adopt to generate copied video. In order to detect rotated or flipping copy videos, rotation and flipping robust region binary pattern (RFR) recently was proposed. But, this RFR has a weakness according to rotated angles. Therefore, in order to overcome this problem, multi region binary patterns are proposed in this paper. The proposed method has the similar performance with the original RFR. But, it showed much higher efficiency for memory spaces.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.607-611
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• 2008

This paper proposes new video signature using spatio-temporal information for copy detection. The proposed video copy detection method is based on concentric circle partitioning method for each key frame. Firstly, key frames are extracted from whole video using temporal bilinear interpolation periodically and each frame is partitioned as a shape of concentric circle. For the partitioned sub-regions, 4 feature distributions of average intensity, its difference, symmetric difference and circular difference distributions are obtained by using the relation between the sub-regions. Finally these feature distributions are converted into binary signature by using simple hash function and merged together. For the proposed video signature, the similarity distance is calculated by simple Hamming distance so that its matching speed is very fast. From experiment results, the proposed method shows high detection success ratio of average 97.4% for various modifications. Therefore it is expected that the proposed method can be utilized for video copy detection widely.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.586-591
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• 2014

In recent years, we can access to video contents anywhere and at any time. Therefore distributed video is easily copied, transformed and republished. Since it brings copyright problem, similarity/duplicate detection and measurement is essential to identify the excessive content duplication. In this paper, we analysed various discernment of video which has been transformed with various ways using MPEG-7 Video Signature. MPEG-7 Video Signature, one of video copy detection algorithms, is block based abstraction. Thus we assume Video Signature is weak for spatial transform. The experiments show that MPEG-7 Video Signature is very weak for spatial transform which could occur general as we have assumed.

• Journal of Digital Convergence
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• v.10 no.5
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• pp.185-191
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• 2012

This study deals with the technical approach related to the protection of digital video contents copyright, which has currently become a major issue in the digital contents market. With the production and distribution of digital video contents rapidly increasing, various policies and technical approaches are being made in relation to the protection of intellectual property rights. The technical approach from a DRM (Digital Rights Management) perspective was made from various angles, but its limitations have also been exposed in terms of convenience and quality. In this study, rather than the existing encoding certification and watermark technologies, it introduces technical approaches from a content-based copy detection method, while suggesting a copy detection method using the representative color sequence. In particular, this study takes into consideration the distribution environment of the domestic video market and deals with the technical approach in a direction that can control the illegal distribution of high quality videos.

• Journal of Broadcast Engineering
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• v.14 no.6
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• pp.661-675
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• 2009

The carelessly and illegally copied contents are raising serious social problem as internet and multimedia technologies are advancing. Therefore, development of video copy detection system must be settled without delay. In this paper, we propose the hierarchical video copy detection method that estimates similarity using statistical characteristics between original video and manipulated(transformed) copy video. We rank according to luminance value of video to be robust to spacial transformation, and choose similar videos categorized as candidate segments in huge amount of database to reduce processing time and complexity. The copy videos generally insert black area in the edge of the image, so we remove rig black area and decide copy or not by using statistical characteristics of original video and copied video with center part of frame that contains important information of video. Experiment results show that the proposed method has similar keyframe accuracy to reference method, but we use less memory to save feature information than reference's, because the number of keyframes is less 61% than that of reference's. Also, the proposed method detects if the video is copied or not efficiently despite expansive spatial transformations such as blurring, contrast change, zoom in, zoom out, aspect ratio change, and caption insertion.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.10-17
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• 2009

This paper proposes a compressed domain signature extraction method which can be used for CBCD (Content Based Copy Detection). Since existing signature extraction methods for the CBCD are executed in spatial domain, they need additional computations to decode the compressed video before the signature extraction. To avoid this overhead, we generate a thumbnail image directly from the compressed video without full decoding. Then we can extract the video signature from the thumbnail image. Experimental results of extracting brightness ordering information as the signature for CBCD show that our proposed method is 2.8 times faster than the spatial domain method while maintaining 80.98% accuracy.