• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.397-401
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• 1997

In this paper, we propose a neural-network that detects moving objects in an image using a diffusion neural network. The proposed neural network is improved by adding a self loop to diffusion layer to remove the noise in an image and to reduce the detection of phantom edge. Computer simulation with real images show that the proposed neural network can extract edges of moving object efficiently.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.67-73
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• 2007

This paper presents a panoramic reference image generation based automatic algorithm for moving objects detection robust to illumination variations under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally. aligning and reorganizing this images. In generation of the cylindrical panoramic image, most of previous works assume the static environment. We propose the method to generating the panoramic reference image from dynamic environments in this paper. We develop an efficient approach for panoramic reference image generation by using accumulated edge map as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The experimental results show that panoramic reference image generation robust to illumination variations can be possible using the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.205-208
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• 2006

The position tracking of moving image for surveillance system is presented in this paper. The image of objects moving is detected with difference image between the background image not to be moved relatively and the forward moving image. The moving image is tracked with edge detection and moving vector to the object. The experiment result shows that the system enable to trail the position of moving objects obviously and is able to discriminate an infiltration.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.137-140
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• 2009

본 논문에서는 Spatial Edge와 Temporal Edge를 이용한 이동 객체의 윤곽선 검출 방법을 제안한다. 카메라로부터 연속적으로 입력되는 영상에서 이동 객체의 윤곽선이 존재하는 후보 영역을 검출하기 위해, 새로운 방법의 Temporal Edge를 제안한다. Temporal Edge를 통해 검출된 후보 영역을 중심으로 Spatial Edge를 구하고, 후처리 과정을 통해 노이즈를 제거한 후 최종적으로 이동 객체의 윤곽선을 검출한다. 제안한 방법은 실험을 통해 그 성능을 확인하였고, 배경 차 방법과 비교 하였다.

• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.3-13
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• 2004

The TPR-tree exploits bounding rectangles based on the function of time in order to index moving objects. As time passes on, each edge of a BR expands with the fastest velocity vector. Since the expansion of the BR results in a serious overlaps between neighboring nodes, the performance of range query is getting worse. In this paper, we propose schemes to reorganize bounding rectangles of nodes. When inserting a moving object, we exploit a forced merging scheme to merge two overlapped nodes and re-split it. When deleting a moving object, we used forced reinsertion schemes to reinsert other objects of a node into a tree. The forced reinsertion schemes are classified into a deleted node reinsertion scheme and an overlapped nodes reinsertion scheme. The overlapped nodes reinsertion scheme outperforms the forced merging scheme and the deleted node reinsertion scheme in all experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.245-249
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• 2010

In the stereo vision system, information about an object could be gained by searching through images. Edges which are based on the information about an object are used to find the position of the object and send a message of its position coordinate to a unmanned crain. This thesis proposes an algorithm to find the center point of the object's surface which is connected to the unmanned crain's arm, and to recognize the shape of the object by using two CCD cameras. At first, getting information about the edges, and distinguishing each edge's characteristics depend on user's option, and then find the location information by a set of positions that are proposed. This thesis is expected to be devoted to the development of an automation system of unmanned moving equipment.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.434-436
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• 2006

In a visual driver-assistance system, separating moving objects from fixed objects are an important problem to maintain multiple hypothesis for the state. Color and edge-based tracker can often be "distracted" causing them to track the wrong object. Many researchers have dealt with this problem by using multiple features, as it is unlikely that all will be distracted at the same time. In this paper, we improve the accuracy and robustness of real-time tracking by combining a color histogram feature with a brightness of Optical Flow-based feature under a Sequential Monte Carlo framework. And it is also excepted from Tracking as time goes on, reducing density by Adaptive Particles Number in case of the fixed object. This new framework makes two main contributions. The one is about the prediction framework which separating moving objects from fixed objects and the other is about measurement framework to get a information from the visual data under a partial occlusion.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.26-34
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• 1998

In this paper, a force control algorithm for edge following task is suggested. Through the contact state modeling between rigid part and end-effector of robot, contact force and contact angle that are essencial parameters to build the control strategies for following movement of end-effector are derived. From these two parameters, we discriminate the every contact state into 8 cases and calculate the new moving position and direction simply. For the experiment. RX90 robot from Staubli with robot language V$^{+}$ is applied and F/T sensor is attached to the wrist of robot with RCC. Finally, 3 edge following experiments including the following of corner point are executed with successful results.s.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.79-84
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• 2005

In this paper, we developed an omni-directional surveillance and motion detection method. The fish-eye lens provides a wide field of view image. Using this image, the equi-distance model for the fish-eye lens is applied to get the perspective and panorama images. Generally, we must consider the trade-off between resolution and field of view of an image from a camera. To enhance the resolution of the result images, some kind of interpolation methods are applied. Also the moving edge method is used to detect moving objects for the object tracking.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1121-1135
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• 2005

This paper proposes a moving object extraction method using the contrast map and salient points. In order to make the contrast map, we generate three-feature maps such as luminance map, color map and directional map and extract salient points from an image. By using these features, we can decide the Attention Window(AW) location easily The purpose of the AW is to remove the useless regions in the image such as background as well as to reduce the amount of image processing. To create the exact location and flexible size of the AW, we use motion feature instead of pre-assumptions or heuristic parameters. After determining of the AW, we find the difference of edge to inner area from the AW. Then, we can extract horizontal candidate region and vortical candidate region. After finding both horizontal and vertical candidates, intersection regions through logical AND operation are further processed by morphological operations. The proposed algorithm has been applied to many video sequences which have static background like surveillance type of video sequences. The moving object was quite well segmented with accurate boundaries.