• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.75-83
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• 2007

A model based approach of tracking the limbs of a walking human subject is proposed in this paper. The tracking process begins by building a data base composed of conditional probabilities of motions between the limbs of a walking subject. With a suitable amount of video footage from various human subjects included in the database, a probabilistic model characterizing the relationships between motions of limbs is developed. The motion tracking of a test subject begins with identifying and tracking limbs from the surveillance video image using the edge and silhouette detection methods. When occlusion occurs in any of the limbs being tracked, the approach uses the probabilistic motion model in conjunction with the minimum cost based edge and silhouette tracking model to determine the motion of the limb occluded in the image. The method has shown promising results of tracking occluded limbs in the validation tests.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.931-932
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• 2008

An implementation of modified stereo matching using efficient belief propagation(BP) algorithm is presented in this paper. Edges of the image were found using conventional edge detection algorithms. Resulting edge information is used to suppress propagation of wrong probabilistic information. Proposed method can effectively reduce errors that incurred by ambiguous scene properties.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.640-646
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• 2003

We presents an edge-based point correlation algorithm for fast and stable visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties in applying automated inspection systems to real factory environment. First of all, NGC algorithms involve highly complex computation and thus require high performance hardware for realtime process. In addition, lighting condition in realistic factory environments is not stable and therefore intensity variation from uncontrolled lights gives many troubles for applying NGC directly as pattern matching algorithm. We propose an algorithm to solve these problems, using thinned and binarized edge data, which are obtained from the original image. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the computational complexity. Matching edges instead of using original gray-level image pixels overcomes problems in NGC method and pyramid of edges also provides fast and stable processing. All proposed methods are proved by the experiments using real images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.45-51
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• 2006

Recently, the IDS(Intrusion Detection System) using a video camera is an important part of the home security systems which start gaining popularity. However, the video intruder detection has not been widely used in the home surveillance systems due to its unreliable performance in the environment with abrupt illumination change. In this paper, we propose an effective moving edge extraction algerian from a sequence image. The proposed algorithm extracts edge segments from current image and eliminates the background edge segments by matching them with reference edge list, which is updated at every frame, to find the moving edge segments. The test results show that it can detect the contour of moving object in the noisy environment with abrupt illumination change.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.37-46
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• 2010

In this paper we have presented a two dimensional model based tracking system using improved chamfer matching. Conventional chamfer matching could not calculate similarity well between the object and image when there is very cluttered background. Then we have improved chamfer matching to calculate similarity well even in very cluttered background with edge and corner feature points. Improved chamfer matching is used as likelihood function of particle filter which tracks the geometric object. Geometric model which uses edge and corner feature points, is a discriminant descriptor in color changes. Particle Filter is more non-linear tracking system than Kalman Filter. Then the presented method uses geometric model, particle filter and improved chamfer matching for tracking object in complex environment. In experimental result, the robustness of our system is proved by comparing other methods.

• Journal of Navigation and Port Research
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• v.32 no.5
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• pp.355-361
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• 2008

Stereo matching is one of the most active research areas in computer vision. In this paper, we propose a stereo matching scheme using genetic algorithm for object depth recognition. The proposed approach considers the matching environment as an optimization problem and finds the optimal solution by using an evolutionary strategy. Accordingly, genetic operators are adapted for the circumstances of stereo matching. An individual is a disparity set. Horizontal pixel line of image is considered as a chromosome. A cost function is composed of certain constraints which are commonly used in stereo matching. Since the cost function consists of intensity, similarity and disparity smoothness, the matching process is considered at the same time in each generation. The LoG(Laplacian of Gaussian) edge is extracted and used in the determination of the chromosome. We validate our approach with experimental results on stereo images.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.10
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• pp.123-131
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• 1999

In this paper, we proposed stereo matching algorithm by dynamic programming with edges emphasized. Existing algorithms show blur generally at depth discontinuities owing to smoothness constraint and non-existence of matching pixel in occlusion regions. Also it accompanies matching error by lackness of matching information in the untextured regions. This paper defines new cost function to make up for the problems occurred to existing algorithms. It is possible through deriving matching of edges in left and right images to be carried out between edge regions anf deriving that in the other regions to be peformed between the other regions. In case of the possibility that edges can be Produced in a large amount, matching between edge information adds weight to cost function in proportion to Path distance. Proposed algorithm was applied to various images obtained by convergent camera model as well as parallel camera model. As the result, proposed algorithm showed improved performance in the aspect of matching error and processing in the occlusion regions compared to existing algorithms. Also it could improve blur especially in discontinuity regions.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.943-946
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• 1998

In this paper, we applied FFT to PCB Images, cutting unnecessary singals and noise, moving the starting point to center of image and used rotaion transform. from the detected edge Hough Transform identify the length, but not the angle, so we matched PCB images with using rotation transform to identify length and angle. After rotation transform we employ Least Squared Method to exact stereo matching.

• Bulletin of the Korean Mathematical Society
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• v.37 no.1
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• pp.121-125
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• 2000

In this paper, we obtain an algorithm for finding a maximum matching in the line graph L(G) of a graph G. The complexity of our algorithm is O($$\mid$E$\mid$$), where is the edge set of G($$\mid$E$\mid$$ is equal to the number of vertices in L(G)).

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.4
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• pp.36-47
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• 1992

In this paper, a set of TM(template matching) mask using the AM(associative mapping) technique was generated and the edge detection algorithm for a SAR image was proposed. And also, the performance of the proposed edge detection algorithm was tested with the conventional edge detection techniques. The proposed edge detection algorithm created an edge image which was more accurate and clear than the conventional edge detection techniques and the performance of the proposed detection technique was not deteriorated for low intensity area in the image because the uncertainly thresholded value genetated by the conventional detection methods was requested. Also, the number of masks and the detection time were reduced by adjusting resolution of edge detection and the consideration for the threshold value extracting the edge was very intuitive.