• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1907-1910
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• 2003

This paper describes a method of stereo image composition for mixed reality without camera calibration or complicate tracking algorithm. The proposed system tracks the panel which has blob makers, and composes virtual objects naturally using the method of texture mapping which is often used in geological computer graphics mapping when we do mapping 2D computer graphic data or man-made 2D images. The proposed algorithm makes it possible for us to compose virtual data even in the case that the panel is bent. For composing 3D object, the system uses depth information obtained from stereo image so that we do not need cumbersome procedure of camera calibration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10B
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• pp.1821-1831
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• 2000

In this paper we propose a new adaptive stereo object tracking system that can extract the object from the complex background and foreground noises by using the image-based SAD algorithm and control the convergence angle and pan/tilt of cameras by using optical BPEJTC. From the experimental results the proposed stereo tracking system is found to track the object adpatively under the circumstance of complex and changing background noises and the possibility of real-time implementation of the proposed system by using the optical system is also suggested.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.117-118
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• 2007

A robot needs a human detection algorithm for interaction with a human. This paper proposes a method that finds people using a SVM (support vector machine) classifier and a stereo camera. Feature vectors of SVM are extracted by HoG (histogram of gradient) within images. After training extracted vectors from the clustered images, the SVM algorithm creates a classifier for human detection. Each candidate for a human in the image is generated by clustering of depth information from a stereo camera and the candidate is evaluated by the classifier. When compared with the existing method of creating candidates for a human, clustering reduces computational time. The experimental results demonstrate that the proposed approach can be executed in real time.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.6
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• pp.26-34
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• 2006

In this paper, We proposed he algorithm for defect extraction and a study of the stereo image modeling o inspect defect for the ball height of BGA(ball grid way) device using 2-dimensional images captured by the BGA device of using the high resolution CCD cameras. This paper propose the package/ball area extraction of BGA device part, the FOV(field of view) calibration part, the top point matching part, and ball height measurement method. Each BGA device propose extraction method by defect, Through the experiment, we verified the result.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1098-1101
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• 2004

The ordinary stereo image of an object consists of data of left and right views. Therefore, the left and right image pairs have to be transmitted simultaneously in order to display 3-dimentional video at the remote site. However, due to the twice data in comparing with a monoscopic image of the same object, it needs to be compressed for fast transmission and resource saving. Hence, it needs an effective coding algorithm for compressing stereo image. It was found previously that compressing left and right frames independently will achieve the compression ratio lower than compressing by utilizing the spatial redundancy between both frames. Therefore, in this paper, we study the stereo image compression technique based on the multiresolution wavelet transform using varied disparity-block size for estimation and compensation. The size of disparity-block in the stereo pair subbands are scaling on a coarse-to-fine wavelet coefficients strategy. Finally, the reference left image and residual right image after disparity estimation and compensation are coded by using SPIHT coding. The considered method demonstrates good performance in both PSNR measures and visual quality for stereo image.

• ETRI Journal
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• v.35 no.6
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• pp.1011-1020
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• 2013

In this paper, we present a method for obtaining a high-quality 3D depth. The advantages of active pattern projection and passive stereo matching are combined and a system is established. A diffractive optical element (DOE) is developed to project the active pattern. Cross guidance (CG) and auto guidance (AG) are proposed to perform the passive stereo matching in a stereo image in which a DOE pattern is projected. When obtaining the image, the CG emits a DOE pattern periodically and consecutively receives the original and pattern images. In addition, stereo matching is performed using these images. The AG projects the DOE pattern continuously. It conducts cost aggregation, and the image is restored through the process of removing the pattern from the pattern image. The ground truth is generated to estimate the optimal parameter among various stereo matching algorithms. Using the ground truth, the optimal parameter is estimated and the cost computation and aggregation algorithm are selected. The depth is calculated and bad-pixel errors make up 4.45% of the non-occlusion area.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.6
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• pp.543-551
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• 2015

In this study, a novel method for dimension measurement of large-scale moving objects using stereo camera with 2-degree of freedom (2-DOF) mechanism is presented. The proposed method utilizes both the advantages of stereo vision technique and the enlarged visibility range of camera due to 2-DOF rotary mechanism in measuring large-scale moving objects. The measurement system employs a stereo camera combined with a 2-DOF rotary mechanism that allows capturing separate corners of the measured object. The measuring algorithm consists of two main stages. First, three-dimensional (3-D) positions of the corners of the measured object are determined based on stereo vision algorithms. Then, using the rotary angles of the 2-DOF mechanism the dimensions of the measured object are calculated via coordinate transformation. The proposed system can measure the dimensions of moving objects with relatively slow and steady speed. We showed that the proposed system guarantees high measuring accuracy with some experiments.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.769-778
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• 2004

Object segmentation is a challenging Problem when the background is cluttered and the objects are overlapped one another. Recent develop-ment using snake algorithms proposed to segment objects from a 2-D Image presents a higher possibilityfor getting better contours. However, the performance of those snake algorithms degrades rapidly when the background is cluttered and objects are overlapped one another, Moreover, the initial snake point placement is another difficulty to be resolved. Here, we propose a novel snake algorithm for object segmentation using disparity information taken from a set of stereo images. By applying our newly designed snake energy function defined in the disparity space, our algorithmeffectively circumvents the limitations found in the previous methods. The performance of the proposed algorithm has been verified by computer simulation using various stereo image sets. The experiment results have exhibited a better performance over the well-known snake algorithm in terms of segmentation accuracy.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.53-62
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• 1998

In this paper, a genetic algorithm-based optimization technique for stereo matching is proposed. Stereo matching is an essential process to recover three-dimensional structure of objects. The proposed two-dimensional chromosomes consist fo disparity values. The cost function of each chromosome is composed of the intensity-difference between two images and smoothness of disparity. The crossover and mutation operators in the two-dimensional chromosomes are described. The operations are affected by the disparities of neighbor pixels. The knowledge-augmented operators are shown to result in rapid convergence and stable result. The genetic algorithm for stereo matching is tested on synthetic and natural images. Experimental results of various images show that the proposed algorithm has good performance even if the images have too dense or sparse feature points. severe noise, and repeating pattern.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.239-246
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• 2005

In this paper. we generate a virtual right image corresponding to the input left image by using given RGB texture data and 8 bit gray scale depth data. We first transform the depth data to disparity data and then produce the virtual right image with this disparity. We also proposed a stereo image synthesis algorithm which is adaptable to a viewer's position and an real-time processing algorithm with a fast LUT(look up table) method. Finally, we could synthesize a total of eleven stereo images with different view points for SD quality of a texture image with 8 bit depth information in a real time.