• International Journal of Automotive Technology
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• v.7 no.3
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• pp.361-367
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• 2006

This paper describes a novel stereo vision based localization of free parking site, which recognizes the target position of automatic parking system. Pixel structure classification and feature based stereo matching extract the 3D information of parking site in real time. The pixel structure represents intensity configuration around a pixel and the feature based stereo matching uses step-by-step investigation strategy to reduce computational load. This paper considers only parking site divided by marking, which is generally drawn according to relevant standards. Parking site marking is separated by plane surface constraint and is transformed into bird's eye view, on which template matching is performed to determine the location of parking site. Obstacle depth map, which is generated from the disparity of adjacent vehicles, can be used as the guideline of template matching by limiting search range and orientation. Proposed method using both the obstacle depth map and the bird's eye view of parking site marking increases operation speed and robustness to visual noise by effectively limiting search range.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.766-771
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• 2004

In this paper, new exploration mobile robot is presented. This mobile robot, called Robhaz-6W, is able to overcome hazardous terrains, recognize three dimensional terrain information and generate a path toward the destination by itself. We develop the passive four bar linkage mechanism adoptable to such terrain without any active control and the real time stereo vision system for obstacle avoidance, a remote control and a path planning method. And the geometrical information is transmitted to the operator in the remote site via wireless LAN equipment. And finally, experimental results for the passive mechanism, the real time stereo vision system, the path planning are reported, which show the versatility of the proposed mobile robot system to carry out some tasks.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• v.11 no.2
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• pp.447-453
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• 2006

This paper presents an area-based stereo algorithm suitable to real time applications. The core of the algorithm depends on the uniqueness constraint and on a matching process that allows for rejecting previous matches. The proposed approach is compared with the left right consistency constraint, being the latter the basic method for detecting unreliable matches in many area-based stereo algorithms. We used the watermelon and tomatoes for experiments.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.202-204
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• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a Transformation algorithm of an Leg-wheel Hexapod Robot is proposed. Robot designed as can have advantages that do transfer possibility fast mobility in flat topography and uneven topography through walk that use wheel drive. In the proposed system, using the disparity data obtained from the left and right images captured by the stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Robot uses construed environmental data and transformation algorithm, decide wheel drive and leg waik, and can calculate width of street and regulate width of robot.

• Journal of Sensor Science and Technology
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• v.13 no.2
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• pp.144-151
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• 2004

In this paper, we propose an active stereo surveillance system with human-like convergence function. The proposed system uses a bottom-up saliency map model with the human-like selective attention visual function to select an interesting region in each camera. and this system compares the landmarks whether the selective region in each camera finds a same region. If the left and right cameras successfully find a same landmarks, the implemented vision system focuses on the landmark. Using the motor encoder information, we can automatically obtain the depth information and resultantly construct a depth map using the depth information. Computer simulation and experimental results show that the proposed convergence method is very effective to implement the active stereo surveillance system.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.10a
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• pp.147-152
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• 1997

This paper presents a method for measuring and analyzing strains in sheet metal forming by stereo vision system. A better understanding and evaluation of the formability can be achieved by analyzing stain distribution in deformed sheet metals. By means of image processing technique, it is possible to get strain distribution efficiently. For measuring strain automatically and accurately, algorithms for camera calibration, grid detection, stereo matching and strain analysis has been developed and verified by experiments with GUI(Graphic User Interface).

• Journal of Information Display
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• v.3 no.2
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• pp.19-25
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• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.28.2-28
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• 2001

Three dimensional shape measurement techniques are widely needed in industries for product quality monitoring and control. X-ray imaging method is a promising technology to achieve three-dimensional Information, both the surface and inner structure of an object, since it can overcome the limitations of conventional visual or optical methods such as an occlusion problem or surface reflection properties. In this paper, we propose three dimensional volume reconstruction method based on x-ray stereo imaging technology. Here, the stereo images of an object from two different views are taken by changing the object pose rather than moving imaging plane as in conventional stereo vision method. We propose a series of image processing techniques to extract the features efficiently from x-ray images, where the occluded features in case of normal camera vision could be found ...

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.170-179
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• 1993

In this study, self-organized neural network is used to solve the vorrespondence problem of the axial stereo image. Edge points are extracted from a pair of stereo images and then the edge points of rear image are assined to the output nodes of neural network. In the matching process, the two input nodes of neural networks are supplied with the coordi- nates of the edge point selected randomly from the front image. This input data activate optimal output node and its neighbor nodes whose coordinates are thought to be correspondence point for the present input data, and then their weights are allowed to updated. After several iterations of updating, the weights whose coordinates represent rear edge point are converged to the coordinates of the correspondence points in the front image. Because of the feature map properties of self-organized neural network, noise-free and smoothed depth data can be achieved.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1411-1422
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• 2003

The detection of free spaces between obstacles in a scene is a prerequisite for navigation of a mobile robot. Especially for stereo vision-based navigation, the problem of correspondence between two images is well known to be of crucial importance. This paper describes multi-range approach of area-based stereo matching for grid mapping and visual navigation in uncertain environment. Camera calibration parameters are optimized by evolutionary algorithm for successful stereo matching. To obtain reliable disparity information from both images, stereo images are to be decomposed into three pairs of images with different resolution based on measurement of disparities. The advantage of multi-range approach is that we can get more reliable disparity in each defined range because disparities from high resolution image are used for farther object a while disparities from low resolution images are used for close objects. The reliable disparity map is combined through post-processing for rejecting incorrect disparity information from each disparity map. The real distance from a disparity image is converted into an occupancy grid representation of a mobile robot. We have investigated the possibility of multi-range approach for the detection of obstacles and visual mapping through various experiments.