• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.295-298
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• 2002

This paper presents a fast block-matching algorithm to improve the conventional Three-Step Search (TSS) based method. The proposed Comparison Fast Block Matching Algorithm (CFBMA) begins with DAB for adaptive search range to choose searching method, and searches a part of search window that has high possibility of motion vector like other partial search algorithms. The CFBMA also considers the opposite direction to reduce local minimum, which is ignored in almost conventional based partial search algorithms. CFBMA uses the summation half-stop technique to reduce the computational load. Experimental results show that the proposed algorithm achieves the high computational complexity compression effect and very close or better image quality compared with TSS, SES, NTSS based partial search algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.45-60
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• 2005

We consider a vehicle routing problem with time window and dock capacity constraints (VRPTD). In most traditional models of vehicle routing problems with time window (VRPTW), each customer must be assigned to only one vehicle route. However demand of a customer may exceed the capacity of one vehicle, hence at least two vehicles may need to visit the customer We assume that each customer has Its own dock capacity. Hence, the customer can be served by only a limited number of vehicles simultaneously. Given a depot, customers, their demands, their time windows and dock capacities, VRPTD is to get a set of feasible routes which pass the depot and some customers such that all demands of each customer are satisfied Since VRPTD is NP-hard, a meta-heuristic algorithm is developed. The algorithm consists of two Procedures : the route construction procedure and the route scheduling procedure. We tested the algorithm on a number of instances and computational results are reported.

• Genomics & Informatics
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• v.8 no.1
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• pp.58-61
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• 2010

CpG is the pair of nucleotides C and G, appearing successively, in this order, along one DNA strand. It is known that due to biochemical considerations CpG is relatively rare in most DNA sequences. However, in particular subsequences, which are a few hundred to a few thousand nucleotides long, the couple CpG is more frequent. These subsequences, called CpG islands, are known to appear in biologically more significant parts of the genome. The ability to identify CpG islands along a chromosome will therefore help us spot its more significant regions of interest, such as the promoters or 'start' regions of many genes. In this respect, I developed the CpG islands search tool, CpG Islands Detector, which was implemented in JAVA to be run on any platform. The window-based graphical user interface of CpG Islands Detector may facilitate the end user to employ this tool to pinpoint CpG islands in a genomic DNA sequence. In addition, this tool can be used to highlight potential genes in genomic sequences since CpG islands are very often found in the 5' regions of vertebrate genes.

• Korean Journal of Remote Sensing
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• v.8 no.1
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• pp.15-26
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• 1992

This paper describes an implementation of adaptive stereo matching for DBM generation. The matching method of two stereo satellite images to find corresponding points used in this paper is area-based matching, which is usually used in the field of making DBM. Same window size and search area used as in the conventional matching methods and we propose adaptive stereo matching algorithm in this paper. We cluster three areas which are consist of mountainous areas, cultivated areas and cities, and rivers and lakes by using proposed linear feature extracting method. These classified areas are matched by adaptive window size and search area, but rivers and lakes is excluded in this experiment. The matching time is three times faster than conventional methods.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.545-552
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• 2012

In this paper, we propose Modified Multi CAMShift Algorithm based on Kalman filter and Weighted Search Windows(KWMCAMShift) that extracts skin color area and tracks several human body parts for real-time human tracking system. We propose modified CAMShift algorithm that generates background model, extracts skin area of hands and head, and tracks the body parts. Kalman filter stabilizes tracking search window of skin area due to changing skin area in consecutive frames. Each occlusion areas is avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed KWMCAMShift algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.43-46
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• 2000

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.501-504
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• 2003

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.69-72
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• 2000

In CDMA systems, the performance of the typical multipath searcher degrades much according as the signal to noise ratio becomes low. In this paper, multipath searcher algorithm is proposed based on sliding window to overcome this drawback. In searcher systems, correlation values between incoming and local PN sequences are used to acquire multipath components. Therefore more accurate distributions of correlation values obtained through this proposed algorithm enables to get higher detection probability. In computer simulations, it is verified that proposed algorithm has better performances in Rayleigh fading channel and Gaussian channel.

• Journal of Astronomy and Space Sciences
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• v.8 no.1
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• pp.115-123
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• 1991

Automatching algorithm is suitable for cross-correlation, which showed correlation surface about maximal correlation coefficient. The size of the window area must be determined empirically, whereas window size generally chosen as a compromise between speed and accuracy. It is possible that epipolar transform prevented from mismatching and decreased search space. In application of the astronomical fields, automatching algorithm mainly used to planet surface recovery in satellite image.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1289-1301
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• 2015

Pedestrian detection (PD) is an essential task in various applications and sliding window-based methods utilizing HOG (Histogram of Oriented Gradients) or HOG-like descriptors have been shown to be very effective for accurate PD. However, due to exhaustive search across images, PD methods based on sliding window usually require heavy computational time. In this paper, we propose a real-time PD method for embedded visual surveillance with fixed backgrounds. The proposed PD method employs HOG descriptors as many PD methods does, but utilizes selective search so that it can save processing time significantly. The proposed selective search is guided by restricting searching to candidate regions extracted from Adaptive Gaussian Mixture Model (AGMM)-based background subtraction technique. Moreover, approximate computation of HOG descriptor and implementation in fixed-point arithmetic mode contributes to reduction of processing time further. Possible accuracy degradation due to approximate computation is compensated by applying an appropriate one among three offline trained SVM classifiers according to sizes of candidate regions. The experimental results show that the proposed PD method significantly improves processing speed without noticeable accuracy degradation compared to the original HOG-based PD and HOG with cascade SVM so that it is a suitable real-time PD implementation for embedded surveillance systems.