• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.4152-4158
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• 2012

The Stereo X-ray inspection system is designed for effectively providing the additional information of objects than the conventional inspection system that offers only 2D cross-section of objects. We studied the geometric improvement of the stereo X-ray inspection system, the stereo matching algorithm of the single object using the edge and the volume reconstruction method for the inspected object. In this paper, we conduct a matching algorithm to find the correspondences between the images and reconstruct 3-D shapes of real objects using the stereo X-ray images. Also, we apply a new 3D reconstruction algorithm for the discrimination of two objects. For the separation of the overlapping objects, we calculate the vector of the object and divide inner and outer voxel of objects. And for the elimination of the overlapping area, we study the reconstruct 3D shapes using the threshold based Z-axis. The experimental results show that the proposed technique can enhance the accuracy of stereo matching and give more efficient visualization for overlap objects in the restricted environment.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.64-74
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• 2014

The primary and ambient signal decomposition of a stereo sound is a key step to the stereo upmix. The principal component analysis (PCA) is one of the most widely used methods of primary-ambient signal decomposition. However, previous PCA-based decomposition algorithms assume that stereo sound sources are only amplitude-panned without any consideration of phase difference. So it occurs some performance degradation in case of live recorded stereo sound. In this paper, we propose a new PCA-based stereo decomposition algorithm that can consider the phase difference between the channel signals. The proposed algorithm overcomes limitation of conventional signal model using PCA with phase alignment. The phase alignment is realized by using inter-channel phase difference (IPD) which is widely used in parametric stereo coding. Moreover, Enhanced Modified PCA(EMPCA) is combined to solve the problem of conventional PCA caused by Primary to Ambient energy Ratio(PAR) and panning angle dependency. The simulation results are presented to show the improvements of the proposed algorithm.

• 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 Broadcast Engineering
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• v.7 no.3
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• pp.229-237
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• 2002

Natural synthesis of real and virtual images is a key technology in mixed reality. For this purpose, we propose an efficient dense disparity estimation algorithm and a synthesis algorithm considering features of stereo images. Dense disparities are estimated hierarchically from the low to high resolution images. In the process, the region-dividing-bidirectional-matching algorithm makes matching process efficient and keeps the reliability of the estimated disparities, and dense disparities are assigned considering edge information. finally, mixed reality stereo images are synthesized by comparing depth data of real and virtual Images. Computer simulation shows that the proposed algorithms estimate very stable disparity vectors with sharp edge and synthesize natural stereo mixed reality images.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.85-90
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• 1998

The most important step image processing is stereo matching process. That is finding pixels of 3 dimensional pair in the left and right image. There are two matching methods. One is an area based approach and the other is a feature based approach. An area based approach needs much calculation time. In the other hand, we have the advantage of calculation time in the feature based approach, but can not obtain matched data for all pixels in the image. In recent years, fuzzy image processing methods are developed to manage vagueness and noise in image and ambiguous, inconsistent knowledge in recognition step. In this paper, we propose a fuzzy stereo matching algorithm. This method converts brightness data of image to fuzzy membership value and processes an area based approach method for stereo matching algorithm. We experiment with some stereo images to validate effectiveness of this algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.2001-2006
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• 2016

The stereo radiation detection system detects the gamma source and acquires two dimensional left and right images for gamma source and visible objects using the detection result. And then the system measures the distance to the radiation source from the system in 3D space using stereo vision algorithm. In this paper, we implemented the fast detection algorithm for gamma source from the system in 3D space to reduce the detection time with image processing algorithms. Additionally, the system's performance is verified through experiments on gamma irradiation facilities. As a result, if the fast detection algorithm applied to the system, we can confirm that the detection system represents a 35% better performance than the conventional detection method that is full scanning to acquire the stereo image. We also have visualized a gamma source distribution through a 3D monitor using the stereo vision algorithm in order to provide the information of radiation spatial distribution to the user efficiently.

• Journal of Satellite, Information and Communications
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• v.7 no.2
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• pp.8-12
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• 2012

Area-based stereo matchng algorithms are widely used for image analysis for stereo vision. SAD (Sum of Absolute Difference) algorithm is one of well known area-based stereo matchng algorithms with the characteristics of data intensive computing application. Therefore, it requires very high computation capabilities and its processing speed becomes very slow with software realization. This paper proposes a fast SAD algorithm utilizing SSE (Streaming SIMD Extensions) instructions based on SIMD (Single Instruction Multiple Data) parallism. CPU supporing SSE instructions has 16 XMM registers with 128 bits. For the performance evaluation of the proposed scheme, we compare the processing speed between SAD with/without SSE instructions. The proposed scheme achieves four times performance improvement over the general SAD, which shows the possibility of the software realization of real time SAD algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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• pp.991-1000
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• 2000

Previous area-based stereo matching algorithms find the disparity by first computing the sum of squared differences (SSD) between corresponding points using a rectangular window, and then searching the position of the minimum SSD within the disparity range. These algorithms generate relatively many matching errors around depth discontinuities, since the SSD function may fail to search for the minimum because of varying disparity profiles in such areas. In this paper, in order to improve the matching accuracy around the depth discontinuities, a new correlation function based on robust estimation technique is proposed for stereo matching. In addition, while previous stereo algorithms utilize a single rectangular window for computing the correlation function, the proposed matching algorithm utilizes 4-directional line masks additionally to reduce the matching errors further. It has been turned out that the proposed algorithm reduces matching errors around depth discontinuities significantly. Experimental results are presented in this paper, comparing the performance of the proposed technique with those of previous algorithms using both synthetic and real images.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1496-1504
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• 2004

In this paper, we propose an algorithm for initializing a target vehicle detection, tracking the vehicle and estimating the distance from it on the stereo images acquired from a forward-looking stereo camera mounted on a road driving vehicle. The process of vehicle detection extracts road region using lane recognition and searches vehicle feature from road region. The distance of tracking vehicle is estimated by TSS correlogram matching from stereo Images. Through the simulation, this paper shows that the proposed method segments, matches and tracks vehicles robustly from image sequences obtained by moving stereo camera.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.716-725
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• 2007

In this paper we describe a motion tracking algorithm for 3D human animation using stereo vision system. This allows us to extract the motion data of the end effectors of human body by following the movement through segmentation process in HIS or RGB color model, and then blob analysis is used to detect robust shape. When two hands or two foots are crossed at any position and become disjointed, an adaptive algorithm is presented to recognize whether it is left or right one. And the real motion is the 3-D coordinate motion. A mono image data is a data of 2D coordinate. This data doesn't acquire distance from a camera. By stereo vision like human vision, we can acquire a data of 3D motion such as left, right motion from bottom and distance of objects from camera. This requests a depth value including x axis and y axis coordinate in mono image for transforming 3D coordinate. This depth value(z axis) is calculated by disparity of stereo vision by using only end-effectors of images. The position of the inner joints is calculated and 3D character can be visualized using inverse kinematics.