• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.767-774
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• 2005

In this paper, we present a snake-based scheme for tracking object contour using disparity information taken from a stereo image sequence with cluttered background. The proposed method is composed of two steps. First, 3-D motion of object is estimated and candidate snake points are selected in disparity space. Second, object contour is extracted by using a modified snake algorithm with disparity information. The proposed algorithm can successfully extract the concave contour of objects and track the object contour in complex image. Performance of the proposed algorithm has been verified by simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2083-2090
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• 2010

This paper presents a 3-D visualization technique using stereo radioactive images to provide efficient inspection of fast moving cargo objects. The proposed technique can be used for such objects which CT or MRI cannot inspect due to restricted scan environment. Stereo radioactive images are acquired from a specially designed equipment which consists of a X-ray source, linear radioactive sensors, and a moving stage. Two radioactive sensors are installed so that rectified stereo X-ray images of objects are acquired. Using the stereo X-ray images, we run a matching algorithm to find the correspondences between the images and reconstruct 3-D shapes of real objects. The objects are put in a parallelepiped box to simulate cargo inspection. Three real objects are tested and reconstructed. Due to the inherent ambiguity in the stereo X-ray images, we reconstruct 3-D shapes of the edges of the objects. The experimental results show the proposed technique can provide efficient visualization for cargo inspection.

• Korean Chemical Engineering Research
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• v.47 no.2
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• pp.179-184
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• 2009

Recent evolution of computer technology enhances the effectiveness of CFD(Computational Fluid Dynamics) analysis for the 3-dimensional complex transport phenomena including turbulent flows. Cheaper and easier than laser and ultra-sonic methods, the windows simulator name by CAMSI(Computer-Aided Management of Stereo Images) has been developed in order to implement the 3-dimensional image using a disparity histogram extracted from left and right stereo images. In our program using the area-based method, the matching pixel finding methods consist of SSD(Sum of Squared Distance), SAD(Sum of Absolute Distance), NCC(Normalized Correlation Coefficient) and MPC(Matching Pixel Count). On performing the program, stereo images on different window sizes for various matching pixel finding methods are compared reasonably. When the image has a small noise, SSD on small window size is more effective. Whereas there is much noise, NCC or MPC is more effective than SSD. CAMSI from the present study will be much helpful to implement the complex objects and to analyze 3-dimensional CFD around them.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.8
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• pp.68-78
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• 1999

In the typical stereo vision system, when the focus points of the left and right images are mismatched or the moving object is not in the center of the image, not only the observer can be fatigued & unconscious of three-dimensional effect, but also hard to track the moving object. Therefore, the stereo object tracking system can be used to track the moving object by controlling convergence angle to minimize stereo disparity and controlling pan/tilt to locate moving object in the center of the image. In this paper, as a new approach to stereo object tracking system we introduce a stereo object tracking simulator based on the optical JTC system capable of adaptive tracking. By using this simulator, any kinds of experimental results can be predicted & analyzed and the processing if real-time implementation of stereo object tracking system is suggested through some optical experiments even if background noises exist.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.9-18
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• 2004

This paper proposes a new and simple stereo matching algorithm using the disparity space image (DSI) technique. First of all, we detect some salient feature points on each scan-line of the image pair and set the matching area using those points and define a simple cost matrix. And we take advantage of matching by pixel-by-pixel instead of using the matching window. While the pixel-by-pixel method boost up the speed of matching, because of no using neighbor information, the correctness of the matching may not be better. To cover this point, we expand the matching path using character of disparity-space-image for using neighbor information. In addition, we devise the compensated matching module using the volume of the disparity space image in order to improve the accuracy of the match. Consequently, we can reduce mismatches at the disparity discontinuities and can obtain the more detailed and correct disparity map.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1235-1238
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• 1998

In television stereo system, to produce the sound image for spatial impression is too difficult because of the narrow distence between two speakers. A method of widening the sound image using precedence effect was introduced but it didn't work effectively in low frequency band. In this paper, we propose a new method to produce an expanded sound image in full band of audio requency in band sound is expanded by phase shifting method and a higher frequency band sound is expanded by reflection. In simulation and experiment, the proposed system guarantees useful effect of sound image expansion in television stereo system.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.304-309
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• 1999

In this paper, we presents a new disparity map refinement algorithm using statistical characteristics of disparity map and edge information. The proposed algorithm generate a refined disparity map using disparity maps which are obtained from area and feature-based Stereo Matching by selecting a disparity value of edge point based on the statistics of both disparity maps. Experimental results on aerial stereo image show the better results than conventional fusion algorithms in the disparity error. This algorithm can be applied to the reconstruction of building image from the high resolution remote sensing data.

• Journal of Biosystems Engineering
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• v.14 no.2
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• pp.104-114
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• 1989

The most important subject in developing agricultural robots for fruit harvesting is to detect accurately the location of a fruit about the given coordinate system. This study was carried out to develop an image processing algorithm which enables finding out the three dimensional locations of a fruit. The digital image processing device consisted of an optosensor (Closed-circuit TV camera), image processing interface board (Digitizer) and microcomputer (IBM PC/AT). A stereo-image processing method using the two cameras attached to the manipulator was evaluated through experiment with apples. The accuracy and quickness of detecting the location of apples by this method was not satisfactory. The maximum errors of the detected locations by the stereo-image processing method in x-, Y-, and z- directions were 3, 4 and 4 cm, respectively. The maximum time required to get the rectangular coordinate data of a fruit was about 2 minutes.

• Journal of Information Display
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• v.5 no.4
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• pp.31-37
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• 2004

In this paper, an effective method for reconstruction of stereoscopic image pair through the regularized adaptive disparity estimation is proposed. Although the conventional adaptive disparity window matching can sharply improve the PSNR of a reconstructed stereo image, but there still exist some problems of overlapping between the matching windows and disallocation of the matching windows, because the size of the matching window tend to changes adaptively in accordance with the magnitude of the feature values. In the proposed method, the problems relating to the conventional adaptive disparity estimation scheme can be solved and the predicted stereo image can be more effectively reconstructed by regularizing the extimated disparity vector with the neighboring disparity vectors. From the experimental results, it is found that the proposed algorithm show improvements the PSNR of the reconstructed right image by about 2.36${\sim}$2.76 dB, on average, compared with that of conventional algorithms.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.115-124
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• 2010

Stereo matching techniques are categorized in two major schemes, local and global matching techniques. In global matching schemes, several investigations are introduced, where cost accumulation is performed in multiple matching lines. In this paper, we introduce a new multi-line stereo matching techniques which expands a conventional single-line matching scheme to multiple one. Matching cost is based on simple normalized cross correlation. We expand the scan-line optimization technique to a multi-line scan-line optimization technique. The proposed technique first generates a reliability image, which is iteratively updated based on the previous reliability measure. After some number of iterations, the reliability image is completed by a hole-filling algorithm. The hole-filling algorithm introduces a disparity score table which records the disparity score of the current pixel. The disparity of an empty pixel is determined by comparing the scores of the neighboring pixels. The proposed technique is tested using the Middlebury and CMU stereo images. The error analysis shows that the proposed matching technique yields better performance than using conventional global matching algorithm.