• 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.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.493-500
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• 2001

Video scene segmentation is fundamental role for content based video analysis. In this paper, we propose a new region based video scene segmentation method using continuity test for each object region which is segmented by the watershed algorithm for all frames in video data. For this purpose, we first classify video data segments into classes that are the dynamic and static sections according to the object movement rate by comparing the spatial and shape similarity of each region. And then, try to segment each sections by grouping each sections by comparing the neighbor section sections by comparing the neighbor section similarity. Because, this method uses the region which represented on object as a similarity measure, it can segment video scenes efficiently without undesirable fault alarms by illumination and partial changes.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.3
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• pp.288-298
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• 2000

Digital assets denote multimedia information that exists in the form of digitized materials such as images, audio, and video. The management of digital assets demands much effort because of a huge amount of storage space requirement and multidimensional characteristics of the information needed to describe their contents. In this paper, we design and implement a Digital Asset Manager that stores and manages digital assets efficiently. Among the various types of digital assets, we focus on the video asset which has the highest complexity. Our Digital Asset Manager provides various facilities for digital contents authoring applications. In the Digital Asset Manager, video assets are managed by using a hierarchical model in order to ensure efficient accesses to any part of a video asset. Our system also guarantees the independence from the storage platform, and provides a fast content-based similarity search method on the digital assets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.758-766
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• 2003

This paper proposes a tree-based hierarchical image mosaicing system using camera and object parameters for efficient video database construction. Gray level histogram difference and average intensity difference are proposed for scene change detection of input video. Camera parameter measured by utilizing least sum of square difference and affine model, and difference image is used for similarity measure of two input images. Also, dynamic objects are searched by through macro block setting and extracted by using region splitting and 4-split detection methods. Dynamic trajectory evaluation function is used for expression of dynamic objects, and blurring is performed for construction of soft and slow mosaic image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.57-64
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• 2006

Motion estimation plays an important role for the compression of video signals. The proposed method utilizes an adaptive threshold and characteristics of a distribution of SAD (sum of absolute difference). Generally, the more complex the SAD distribution is, the larger SAD value tends to be. This proposed algorithm tries to reduce the search points in a simple distribution but increase them in a complex distribution to avoid local minima. A macro block is divided into 9 areas. One of them chosen using spatio-temporal correlation is called the primary area and the others are called the secondary area that will be searched to avoid local minima. The proposed algorithm decides if just one area (the primary area or the secondary area) will be enough to be searched or both areas should be searched, using adaptive threshold. Compared with famous motion estimation algorithms, the simulation result shows that the searching points per macro block and MSE decreases about 16.4% and 32.83 respectively on the average.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1563-1571
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• 2009

In this paper, we propose a new boundary matching method for the temporal error concealment and a post processing algorithm for perceptual quality improvement of the concealed frame. Temporal error concealment is a method that substitutes error blocks with similar blocks from the reference frame. In conventional H.264/AVC standard, it compares outside pixels of erroneous block with inside pixels of reference block to find the most similar block. However, it is very possible that the conventional method substitutes erroneous block with the wrong one because it compares only narrow spatial range of pixels. In this paper, for substituting erroneous blocks with more correct blocks, we propose enhanced boundary matching method by comparing inside and outside pixels of reference block with outside pixels of erroneous block and setting up additional candidate motion vector in the fixed search range based on maximum and minimum value of candidate motion vectors. Furthermore, we propose a post processing method to smooth edges between concealed and decoded blocks without error by using the modified deblocking filter. We identified that the proposed method shows quality improvement of about 0.9dB over the conventional boundary matching methods.