• Journal of the Korea Computer Industry Society
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• v.2 no.3
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• pp.389-396
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• 2001

In detection of a scene change of the moving pictures which has massive information capacity, the temporal sampling method has a faster searching speed and lower missing scene change detection than the sequential searching method for the whole moving pictures, yet employed searching algorithm and detection interval greatly affect missing frame and searching precision. In this study, the whole moving pictures were primarily retrieved threshold by the temporal difference of histogram scene change detection method. We suggested a dynamic threshold algorithm using cut detection interval and derived an equation formula to determine optimal primary retrieval threshold which can cut detection interval computation. Experimental results show that the proposed dynamic threshold algorithm using cut detection interval method works up about 30 percent in precision of performance than the sequential searching method.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1703-1712
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• 1999

In the paper, we propose efficient article and scene change detection algorithms to make the index of sports news compressed in MPEG-2 domain. In the proposed algorithm, the information in MPEG-2 compressed domain is directly used without decoding to save the computation time. The scene change detection algorithm is constructed in an hierarchical method so that the time for detection can be greatly reduced. Also, the algorithm can provide the robust detection against abrupt illuminance change because the luminance and chrominance components are simultaneously considered. Also, the scene change caused by special effect such as dissolve and wipe can be detected in the compressed domain. In the article detection, the algorithm is constructed for robust detection of the anchor frame using the concept of CCV(Color Coherent Vector).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1199-1203
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• 2012

This paper proposes a Scene Change Detection method using the local decision tree and clustering. The local decision tree detects cluster boundaries wherein local scenes occur, in such a way as to compare time similarity distributions among the difference values between detected scenes and their adjacent frames, and group an unbroken sequence of frames with similarities in difference value into a cluster unit.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.75-82
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• 2002

Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper Propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with χ2 histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.89-95
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• 2013

Smoking in elevators is a criminal offense that is included in a misdemeanor. Because of that smoking in elevators can be very critical for our growing children and weak women. In this paper, we would like to extract criminals doing this criminal offense to smoke in elevators. Extraction method detect difference value using modified color-X2-test and it was normalized. Next, we find frames that has occurred scene change in successive frames using the four-step algorithm of scene change detection. Finally, we present the method of smoking image retrieval and extraction in stored large amount of video. In the experiment, we show process and number of scene change detection, and the number of video searched per retrieval time. The extracted smoking video is to submit as evidence for the police or court.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1567-1576
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• 1999

In this paper, we propose new methods to detect a scene cut and a dissolve region in compressed MPEG video sequences. The scene cut detection method uses edge images obtained using DCT AC coefficients and the dissolve detection method utilizes the macroblock type information of the MPEG stream. The proposed scene cut detection method is insensitive to brightness and can detect scene changes more precisely than the methods using DC coefficients since AC edge images can express original images more exactly than DC edge images do. The proposed dissolve detection method using the number of intra macroblocks(MBs) computationally efficient since it does not require the decoding process. Experimental results show that the proposed methods perform better in detection scene changes than conventional other methods.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.304-308
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• 2001

The increase of video data makes the demand of efficient retrieval, storing, and browsing technologies necessary. In this paper, a video segmentation method (scene change detection method, or shot boundary detection method) for the development of such systems is proposed. For abrupt cut detection, inter-frame similarities are computed using luminance and edge histograms and a cut is declared when the similarities are under th predetermined threshold values. A gradual scene change detection is based on the similarities between the current frame and the previous shot boundary frame. A correlation method is used to obtain universal threshold values, which are applied to various video data. Experimental results show that propose method provides 90% precision and 98% recall rates for abrupt cut, and 59% precision and 79% recall rates for gradual change.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.74-81
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• 2005

As the multimedia data increases, various scene change detection algorithms for video indexing and sequence matching have been proposed to efficiently manage and utilize digital media. In this paper, we propose a robust scene change detection algorithm for video sequences with abrupt luminance variations. To improve the accuracy and to reduce the computational complexity of video indexing with abrupt luminance variations, the proposed algorithm utilizes edge features as well as color features, which yields a remarkably better performance than conventional algorithms. In the proposed algorithm first we extract the candidate shot boundaries using color histograms and then determine using edge matching and luminance compensation if they are shot boundaries or luminance changes. If the scene contains trivial brightness variations, the edge matching and luminance compensation are performed only for shot boundaries. In experimental results, the proposed method gives remarkably a high performance and efficiency than the conventional methods with the similar computational complexity.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.534-542
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• 1999

A sell-designed rate control strategy can improve overall picture quality for video transmission over a constant bit rate channel and the rate control method is not a normative part of MPEG-video standard, the performance of MPEG video codec can be quite different depends on how to implement the rate control scheme. The rate control scheme proposed in MPEG show good results when scene changes is not occurred. But it has weakness that it does not properly handle scene-changed pictures. Therefore picture quality after scene change is deteriorated, and possibility of overflow occurrence becomes high. In this paper, a new method for detection of scene change occurrence using local variance and a new determination scheme for adaptive quantization parameter, mqunt, which can consider local characteristic of an image by using previously computed the local variance from the scene change detection part are proposed. IN addition, and adaptive rate control scheme which can handles scene changed picture very efficiently by scene-changed picture is proposed. Computer simulations are performed to verify the performance of the proposed algorithm. The suggested detection algorithm precisely detected scene change. And the proposed rate control scheme shows better rate control performance as compared with that of the conventional MPEG scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1361-1369
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• 1996

Motion estimation is one of the key components for high quality video coding. In this paper, a new motion estimation scheme for MPEG-like video coder is suggested. The proposed temporally adaptive motion estimation scheme consists of five functional blocks: Temporal subband analysis (TSBA), extraction of temporal information, scene change detection (SCD), picture type replacement (PTR), and temporally adapted block matching algorithm (TABMA). Here all the functional components are based on the temporal subband analysis. In this papre, we applied the analysis part of subband decompostion to the temporal axis of moving picture sequence, newly defined the temporal activity distribution (TAD) and average TAD, and proposed the temporally adapted block matching algorithm, the scene change detection algorithm and picture type replacement algorithm which employed the results of the temporal subband analysis. A new block matching algorithm TABMA is capable of controlling the block matching area. According to the temporal activity distribution of objects, it allocates the search areas nonuniformly. The proposed SCD and PTR can prevent unavailable motion prediction for abrupt scene changes. Computer simulation results show that the proposed motion estimation scheme improve the quality of reconstructed sequence and reduces the number of block matching trials to 40% of the numbers of trials in conventional methods. The TSBA based scene change detection algorithm can detect the abruptly changed scenes in the intentionally combined sequence of this experiment without additional computations.