• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.1
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• pp.201-210
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• 2003

In this paper, we propose a new binocular stereo correspondence method by maximizing a fitness formulated by integrating two constraints of edge similarity and disparity smoothness simultaneously. The proposed stereopsis focusing to measure distances to leading vehicles on roads uses intensity gradients as matching attribute. In contrast to the previous work of area-based stereo matching, in which matching unit is a pixel, the matching unit of the proposed method becomes an area itself which is obtained by selecting a series of pixels enclosed by two pixels on the left and right boundaries of an object. This approach allows us to cope with real-time processing and to avoid window size selection problems arising from conventional area-based stereo.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2438-2446
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• 1999

Most of block based stereo pair compression schemes utilize the constant block size and searching area size for all the stereo pairs to find the best matching block. However, it is not efficient to use the same block size and size of searching area to all the stereo pairs, since each stereo pair has different disparity. In this Paper, we propose a method to calculate the total disparity of stereo pairs, and show how to determine the size of the block and searching area which are applied for the block based compression of the stereo pairs.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.277-285
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• 2004

We present a new hybrid stereo matching technique in terms of the co-operation of area-based stereo and feature-based stereo. The core of our technique is that feature matching is carried out by the reference of the disparity evaluated by area-based stereo. Since the reference of the disparity can significantly reduce the number of feature matching combinations, feature matching error can be drastically minimized. One requirement of the disparity to be referenced is that it should be reliable to be used in feature matching. To measure the reliability of the disparity, in this paper, we employ the self-consistency of the disunity Our suggested technique is applied to the detection of 3D line segments by 2D line matching using our hybrid stereo matching, which can be efficiently utilized in the generation of the rooftop model from urban imagery. We carry out the experiments on our hybrid stereo matching scheme. We generate synthetic images by photo-realistic simulation on Avenches data set of Ascona aerial images. Experimental results indicate that the extracted 3D line segments have an average error of 0.5m and verify our proposed scheme. In order to apply our method to the generation of 3D model in urban imagery, we carry out Preliminary experiments for rooftop generation. Since occlusions are occurred around the outlines of buildings, we experimentally suggested multi-image hybrid stereo system, based on the fusion of 3D line segments. In terms of the simple domain-specific 3D grouping scheme, we notice that an accurate 3D rooftop model can be generated. In this context, we expect that an extended 3D grouping scheme using our hybrid technique can be efficiently applied to the construction of 3D models with more general types of building rooftops.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.69-72
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• 2001

This paper proposes a positional estimation method for extracted line features by stereo vision. Based on given reference plane, planar surfaces corresponding the given plane are first extracted. Then, features in the planar surfaces are selected. Using the Extended Kalman Filter the feature positions are estimated by combining area- and feature-based stereo matching results. Experimental results show the proposed method is feasible.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1678-1680
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• 2002

Stereo matching technique is used in many practical fields like satellite image analysis and computer vision. In this paper, we suggest a method to extract a target object image from a complicated background. For example, human face image can be extracted from random background. This method can be applied to computer vision such as security system, dressing simulation by use of extracted human face, 3D modeling, and security system. Many researches about stereo matching have been performed. Conventional approaches can be categorized into area-based and feature-based method. In this paper, we start from area-based method and apply area tracking using scanning window. Coarse depth information is used for area merging process using area searching data. Finally, we produce a target object image.

• Journal of Digital Contents Society
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• v.5 no.4
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• pp.257-263
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• 2004

This paper is related to the object-based stereo matching algorithm which makes it possible to estimate inner-region disparities for each segmented region. First, several sample points are selected for effectively representing the segmented region, Next, stereo matching is applied to the small area within segmented region which existed in the neighborhood or each sample point. Finally, inner-region disparities are interpolated using a plane equation with disparity of each selected sample. According to the proposed method, the problem of feature-based method that the depth estimation is possible only in the feature points can be solved through the propagation of the disparity in the sample point into the inside of the region. Also, as selecting sample points in contour of segmented region we can effectively suppress obscurity which is occurred in the depth estimation of the monotone region in area-based methods.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.293-293
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• 2010

In this paper, we propose a stereo vision based monitoring concept for passenger's safety on railroad platform. In general, basic concept of stereo image processing technique uses the correlations between left and right images, and extracts additional distance information. It provides easy removal of ambient illumination changes, which has been difficult to achieve with conventional 2D based image processing technique. In the paper, we present developed stereo camera and stereo vision based detection algorithm in order to monitor possible accidents at platform area, and verified the detection performance of proposed system with experimental results.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.73-76
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• 2008

We present a area-based method for stereo matching using varying weights. A central problem in a area-based stereo matching is different result from selecting a window size. Most of the previous window-based methods iteratively update windows. However, the iterative methods very sensitive the initial disparity estimation and are computationally expensive. To resolve this problem, we proposed a new function to assign weights to pixels using features. To begin with, we extract features in a given stereo images based on edge. We adjust the weights of the pixels in a given window based on correlation of the stereo images. Then, we match pixels in a given window between the reference and target images of a stereo pair. The proposed method is compared to existing matching strategies using both synthetic and real images. The experimental results show the improved accuracy of the proposed method.