• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2531-2533
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• 2005

The proposed neural network technique is the real time computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objects during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of objects. All of therm request much memory space and time. Therefore the most reliable neural-network algorithm is drived for real-time matching of obejects, which is composed of a dynamic programming algorithm based on sequence matching techniques in moving objects.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.729-734
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• 2005

One of the important research issues in mobile robot is how to detect the 3D environment fast and accurately, and recognize it. Sensing methods of utilizing laser structured light and/or stereo vision are representatively used among a number of methodologies developed to date. However, the methods are still in need of achieving high accuracy and reliability to be used for real world environments. In this paper to implement a new robotic environmental sensing algorithm is presented by combining the information between intensity image and that of laser structured light image. To see how effectively the algorithm applied to real environments, we developed a sensor system that can be mounted on a mobile robot and tested performance for a series of environments.

• Journal of Korea Multimedia Society
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• v.9 no.10
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• pp.1296-1303
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• 2006

The range-based method is easy to get the 3D data in detail, but the image-based is not. In this paper, I suggests the new approach to get the 3D data in detail from the magnified stereo image. Main idea is using the magnifying lens. The magnifying lens not only magnifies the object but also increases the depth resolution. The relation between the amplification of the disparity and the increase of the depth resolution is verified mathematically and the method to improve the original 3D data is suggested.

• 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 Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.935-940
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• 2002

For robot navigation and visual reconstruction, structure from motion (SFM) is an active issue in computer vision community and its properties arc also becoming well understood. In this paper, when using stereo image sequence and direct method as a tool for SFM, we present a new method for overcoming bas-relief ambiguity. We first show that the direct methods, based on optical flow constraint equation, are also intrinsically exposed to such ambiguity although they introduce robust methods. Therefore, regarding the motion and depth estimation by the robust and direct method as approximated ones. we suggest a method that refines both stereo displacement and motion displacement with sub-pixel accuracy, which is the central process f3r improving its ambiguity. Experiments with real image sequences have been executed and we show that the proposed algorithm has improved the estimation accuracy.

• IE interfaces
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• v.11 no.2
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• pp.93-106
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• 1998

This paper suggests a stereo vision-based algorithm for the 3-dimensional inspection of a crimped terminal. The crimped terminal is one of wire harness assemblies which transmit current or signals between a pair of electrical or electronic assemblies. Four types of nonconformities considered includes terminal rolling, band up/down, twist, and crimp height. To obtain stereo image correspondence, an algorithm using Hough transform is proposed. Coordinate transform is then applied to evaluate the degree of 3-dimensional nonconformities. The algorithm has been successfully tested on a number of real specimens collected from a wire harness factory. The test results show the feasibility of the proposed algorithm.

• 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.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.256-267
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• 2017

An active research area in computer vision, stereo matching is aimed at obtaining three-dimensional (3D) information from a stereo image pair captured by a stereo camera. To extract accurate 3D information, a number of studies have examined stereo matching algorithms that employ adaptive support weight. Among them, the adaptive census transform (ACT) algorithm has yielded a relatively strong matching capability. The drawbacks of the ACT, however, are that it produces low matching accuracy at the border of an object and is vulnerable to noise. To mitigate these drawbacks, this paper proposes and analyzes the features of an improved stereo matching algorithm that not only enhances matching accuracy but also is also robust to noise. The proposed algorithm, based on the ACT, adopts the truncated absolute difference and the multiple sparse windows method. The experimental results show that compared to the ACT, the proposed algorithm reduces the average error rate of depth maps on Middlebury dataset images by as much as 2% and that is has a strong robustness to noise.

• International Journal of Automotive Technology
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• v.5 no.4
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• pp.277-285
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• 2004

This paper describes an intelligent mirror adjustment system that rotates a pair of side mirrors and the room mirror of a car to the optimal position for a driver by using the location of the driver's pupils. A stereo vision system measures the three-dimensional coordinates of a pair of pupils by analyzing the input images of stereo B/W CCD cameras mounted on the instrument panel. This system determines the position angle of each mirror on the basis of information about the location of the pupils and rotates each mirror to the appropriate position by mirror actuators. The vision system can detect the driver's pupils regardless of whether it is daytime or nighttime by virtue of an infrared light source. Information about the pair of nostrils is used to improve the correctness of pupil detection. This system can adjust side mirrors and the room mirror automatically and rapidly by a simple interface regardless of driver replacement or driver's posture. Experiment has shown this to be a new mirror adjustment system that can make up for the weak points of previous mirror adjustment systems.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.641-646
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• 2010

This paper presents algorithms for real-time navigation of a humanoid robot with a stereo vision but no other sensors. Using the algorithms, a robot can recognize its 3D environment by retrieving SIFT features from images, estimate its position through the Kalman filter, and plan its path to reach a destination avoiding obstacles. Our approach focuses on estimating the robot’s central walking path trajectory rather than its actual walking motion by using an approximate model. This strategy makes it possible to apply mobile robot localization approaches to humanoid robot localization. Simple collision free path planning and motion control enable the autonomous robot navigation. Experimental results demonstrate the feasibility of our approach.