• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.15-17
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• 2006

This paper presents a new global intensity compensation method for extracting moving object in a visual surveillance system by compensating time variant intensity changes of background region. The method that compensates a little changes of intensity due to time variant illumination change and automatic gain control of camera is called global intensity compensation. The proposed method expresses global intensity change with a mapping table to describe complex form of intensity change while the previous method models this global intensity change with a simple function as a straight line. The proposed method builds the mapping table by calculating the cross histogram between two images and then by selecting an initial point for generating the mapping table by using Hough transform applied to the cross histogram image. Then starting from the initial point, the mapping table is generated according to the proposed algorithm based on the assumption that reflects the characteristic of global intensity change. Experimental results show that the proposed method makes the compensation error much smaller than the previous GIC method

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.101-112
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• 2005

As we perceive the world as 3-dimensional through our two eyes, we can extract 3-dimensional information from stereo images obtained from two or more cameras. Since stereo images have a large amount of data, with recent advances in digital video coding technology, efficient compression algorithms have been developed for stereo images. In order to compress stereo images and to obtain 3-D information such as depth, we find disparity vectors by using disparity estimation algorithm generally utilizing pixel differences between stereo pairs. However, it is not unusual to have stereo images having different intensity values for several reasons, such as incorrect control of the iris of each camera, disagreement of the foci of two cameras, orientation, position, and different characteristics of CCD (charge-coupled device) cameras, and so on. The intensity differences of stereo pairs often cause undesirable problems such as incorrect disparity vectors and consequent low coding efficiency. By compensating intensity differences between left and right images, we can obtain higher coding efficiency and hopefully reduce the perceptual burden of brain to combine different information incoming from two eyes. We propose several methods of intensity compensation such as local intensity compensation, global intensity compensation, and hierarchical intensity compensation as very simple and efficient preprocessing tool. Experimental results show that the proposed algerian provides significant improvement in coding efficiency.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.102-110
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• 2009

In this paper, we propose an object detection method for real-time in infrared (IR) images and PowerPC (PPC) and H/W design based on field programmable gate array (FPGA). An open H/W architecture has the advantages, such as easy transplantation of HW and S/W, support of compatibility and scalability for specification of current and previous versions, common module design using standardized design, and convenience of management and maintenance. Proposed background modeling for an open H/W architecture design decreases size of search area to construct a sparse block template of search area in IR images. We also apply to compensate for motion compensation when image moves in previous and current frames of IR sensor. Separation method of background and objects apply to adaptive values through time analysis of pixel intensity. Method of clutter reduction to appear near separated objects applies to median filter. Methods of background modeling, object detection, median filter, labeling, merge in the design embedded system execute in PFC processor. Based on experimental results, proposed method showed real-time object detection through global motion compensation and background modeling in the proposed embedded system.