• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.407-415
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• 2012

In this paper, we propose a new stereo matching algorithm by using color information especially for stereo images containing human beings in the applications such as tele-presence system. In the proposed algorithm, we first remove the background regions by using a threshold value for stereo images obtained by stereo camera and then find an initial disparity map and segment a given image into R, G, B and white color components. We also obtain edges in the segmented image and estimate the disparity from the extract boundary regions. Finally, we generate the final disparity map by properly combining the disparity map of each color component. Experiment results show better performance compared with the window based method and the dynamic programing method especially for stereo images with human being.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.411-417
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• 2005

In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the potion of the target using a stereo vision system. While a monocular vision system needs properties such as geometric shape of a target, a stereo vision system enables the robot to find the position of a target without additional information. Many algorithms have been studied and developed for an object recognition. However, most of these approaches have a disadvantage of the complexity of computations and they are inadequate for real-time visual servoing. Color information is useful for simple recognition in real-time visual servoing. This paper addresses object recognition using colors, stereo matching method to reduce its calculation time, recovery of 3D space and the visual servoing.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.4
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• pp.16-25
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• 2000

In this paper, a new disparity detection algorithm which is robust to noise is presented. It detects the disparity of an arbitrary pixel through the iterative competition with neighbor pixels in the range of disparity. A diffusion process to improve stereo matching confidence is used prior to detecting disparity of an arbitrary pixel. It is used for aggregating initial matching measure of the difference map. If the image region for matching is too small, a wrong match might be found due to noise. On the contrary, the region is too big, it results in blurring of object boundaries. Therefore, we decide the image region for matching by using the diffusion process for aggregating matching measure, then detect the true disparity with proposed competition method to the distribution of matching measure. Through the proposed method we get the result of improving matching rate of 6.96% with real stereo imge. From the simulation with the stereo imge, the proposed disparity detection method significantly outperforms the conventional method to matching rate.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.461-472
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• 2005

In this paper, we propose face feature extraction algorithm through stereo image's matching value. The proposed algorithm detected face region by change the RGB color space of skin color information to the YCbCr color space. Applying eye-template from extracted face region geometrical feature vector of feature about distance and lean, nose and mouth between eye extracted. And, Proposed method could do feature of eyes, nose and mouth through stereo image's matching as well as 2D feature information extract. In the experiment, the proposed algorithm shows the consistency rate of 73% in distance within about 1m and the consistency rate of 52%in distance since about 1m.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.389-394
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• 2002

In this paper, we propose a robust stereo matching algorithm using nonlinear extended Kalman filter. The proposed algorithm estimates disparity using nonlinear extended Kalman filter and compares left image to right image for obtained disparity. As this process is run iteratively, we get disparity only with a few search. And, we can get robust stereo matching results by comparing left image to right image using bilinear interpolation to consider influence of neighborhood pixel. We compared SSD algorithm which is widely used, in stereo matching method, to result of the proposed algorithm. As the result, the proposed algorithm has an outstanding matching performance.

• 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 KSRS Conference
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• v.2
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• pp.772-775
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• 2006

Muilti-dimensional feature vector matching algorithm uses multiple features such as intensity, gradient, variance, first or second derivative of a pixel to find correspondence pixels in stereo images. In this paper, we proposed a new method for adjusting automatically the weight of feature in multi-dimensional feature vector matching considering sharpeness of a pixel in feature vector distance curve. The sharpeness consists of minimum and maximum vector distances of a small window mask. In the experiment we used IKONOS satellite stereo imagery and obtained accurate matching results comparable to the manual weight-adjusting method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.461-469
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• 2001

Existing area-based stereo algorithms rely heavily on rectangular windows for computing correspondence. While the algorithms with the rectangular windows are efficient, they generate relatively large matching errors due to variations of disparity profiles near depth discontinuities and doesnt take into account local deformations of the windows due to projective distortion. In this paper, in order to deal with these problems, a new correlation function with 4 directional line masks, based on robust estimator, is proposed for the selection of potential matching points. These points is selected to consider depth discontinuities and reduce effects on outliers. The proposed matching method finds an arbitrarily-shaped variable window around a pixel in the 3d array which is constructed with the selected matching points. In addition, the method take into account the local deformation of the variable window with a constant disparity, and perform the estimation of sub-pixel disparities. Experiments with various synthetic images show that the proposed technique significantly reduces matching errors both in the vicinity of depth discontinuities and in continuously smooth areas, and also does not be affected drastically due to outlier and noise.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.77-87
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• 1996

Existing area-based stereo matching algorithms utilize a single rectangular correlation area for computing cross-correlation between corresponding points in stereo images, and compute disparity by finding the peak in the vicinity of depth discontinuity, since, because of inconstnat disparities around discontinuities, the cross-correlation becomes low in such area. Inthis paper, a new area-based matching strategy is proposed exploiting multiple directional correlation masks instead of a single one. The proposed technique computes multiple cross-covariance functions using each oriented mask. Peaks are detected from each covariance function and the disparity is computed by choosing the location with the highest covariance value. Proposed approach can also be applied to compute disparity gradients without obtaining dense depth data. A number of examples are presented using synthetic and natural stereo images.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.265-266
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• 1998

This paper describes a depth extraction algorithm in the stereo endoscopic images using adaptive window. First, The relation between the 3D coordinates in the world and the 2D coordinates in the image plane is estimated using camera calibration. Next, stereo matching is performed to find the conjugate pairs in the left and right images. To improve the precision of the matching result, adaptive window which can be varied on the shape as well as on the size according to the area characteristics is used. Finally, the result from the stereo matching and that of camera modeling are combined to extract the real depth information.