• JSTS:Journal of Semiconductor Technology and Science
• /
• v.12 no.2
• /
• pp.212-218
• /
• 2012

A stereo vision is able to build three-dimensional maps of its environment. It can provide much more complete information than a 2D image based vision but has to process, at least, that much more data. In the past decade, real-time stereo has become a reality. Some solutions are based on reconfigurable hardware and others rely on specialized hardware. However, they are designed for their own specific applications and are difficult to extend their functionalities. This paper describes a vision system based on a System on a Chip (SoC) platform. A real-time stereo image correlator is implemented using Sum of Absolute Difference (SAD) algorithm and is integrated into the vision system using AMBA bus protocol. Since the system is designed on a pre-verified platform it can be easily extended in its functionality increasing design productivity. Simulation results show that the vision system is suitable for various real-time applications.

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

• The Journal of the Acoustical Society of Korea
• /
• v.18 no.2
• /
• pp.66-76
• /
• 1999

This paper proposes that can take at high speed the information of binocular disparity with moving translational and forward stereo camera to the extent that does not occur the problem of a correspondence point. It shows that in case of stereo vision with translational motion, can take the information of binocular disparity being devoid of error and putting high confidence in, and that in case of stereo vision with forward motion, can take the horizontal component which can not be detected in common stereo vision. Besides, the stereo vision can be done at high speed due to being bright and small a correspondence point comparing not to do, because a correspondence between right and left images is previously limited. But there are problem that a resonable information of binocular disparity can not be taken, if the vicinity of center of image is in accord with the region of occlusion in stereo vision with forward motion.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.26 no.2
• /
• pp.223-229
• /
• 2017

Recently, robotic bin-picking tasks have drawn considerable attention, because flexibility is required in robotic assembly tasks. Generally, stereo camera systems have been used widely for robotic bin-picking, but these have two limitations: First, computational burden for solving correspondence problem on stereo images increases calculation time. Second, errors in image processing and camera calibration reduce accuracy. Moreover, the errors in robot kinematic parameters directly affect robot gripping. In this paper, we propose a method of correcting the bin-picking error by using trinocular vision system which consists of two stereo cameras andone hand-eye camera. First, the two stereo cameras, with wide viewing angle, measure object's pose roughly. Then, the 3rd hand-eye camera approaches the object, and corrects the previous measurement of the stereo camera system. Experimental results show usefulness of the proposed method.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.16 no.5
• /
• pp.134-140
• /
• 2017

Shape-from-shading (SFS) or stereo vision algorithms can be utilized to measure the shape of an object with imaging techniques for effective sensing in non-contact measurements. SFS algorithms could reconstruct the 3D information from a 2D image data, offering relatively comprehensive information. Meanwhile, a stereo vision algorithm needs several feature points or lines to extract 3D information from two 2D images. However, to measure the size of an object with a freeform surface, the two algorithms need some additional information, such as boundary conditions and grids, respectively. In this study, a stereo vision scheme using the depth information obtained by shape-from-shading as patterns was proposed to measure the size of an object with a freeform surface. The feasibility of the scheme was proved with an experiment where the images of an object were acquired by a CCD camera at two positions, then processed by SFS, and finally by stereo matching. The experimental results revealed that the proposed scheme could recognize the size and shape of freeform surface fairly well.

• Journal of Advanced Navigation Technology
• /
• v.17 no.3
• /
• pp.354-360
• /
• 2013

A stereo vision analysis was performed for motion and depth control of unmanned vehicles. In stereo vision, the depth information in three-dimensional coordinates can be obtained by triangulation after identifying points between the stereo image. However, there are always triangulation errors due to several reasons. Such errors in the vision triangulation can be alleviated by careful arrangement of the camera position and orientation. In this paper, an approach to the determination of the optimal position and orientation of camera is presented for unmanned vehicles.

• Journal of Advanced Marine Engineering and Technology
• /
• v.36 no.5
• /
• pp.674-682
• /
• 2012

A new intelligent stereo vision sensor system was studied for the motion and depth control of unmanned vehicles. A new bottom-up saliency map model for the human-like active stereo vision system based on biological visual process was developed to select a target object. If the left and right cameras successfully find the same target object, the implemented active vision system with two cameras focuses on a landmark and can detect the depth and the direction information. By using this information, the unmanned vehicle can approach to the target autonomously. A number of tests for the proposed bottom-up saliency map were performed, and their results were presented.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.763-764
• /
• 2008

Sensing is an important part of a smart home system. Vision sensors are a type of passive systems, which are not sensitive to noise. In this paper, we implement a prototype for stereo vision systems using OpenCV. It is an open source library for computer vision developed by Intel corporation. The prototype will by used for comparing performance among various stereo algorithms and for developing a stereo vision smart camera.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.6
• /
• pp.605-611
• /
• 2019

3D Vision system has many applications recently but popularization have many problems that need to be overcome. Volumetric display may process a amount of visual data and design the high efficient vision system for display. In case of stereo system for volumetric display, disparity vectors from the stereoscopic sequences and residual images with the reference images has been transmitted, and the reconstructed stereoscopic sequences have been displayed at the receiver. So central issue for the design of efficient volumetric vision system lies in selecting an appropriate stereo matching and robust vision system. In this paper, we propose high efficient vision system with the reduction of rectification error which can perform the 3D data extraction efficiently with low computational complexity. In experimental results with proposed vision system, the proposed method can perform the 3D data extraction efficiently with reducing rectification error and low computational complexity.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.4 no.1
• /
• pp.25-31
• /
• 2008

In this paper, we propose a new method that separates background and foreground from stereo images. This method can be improved automatic target tracking system by using disparity map of the stereo vision system and background-separating mask, which can be obtained camera configuration parameters. We use disparity map and camera configuration parameters to separate object from background. Disparity map is made with block matching algorithm from stereo images. A morphology filter is used to compensate disparity error that can be caused by occlusion area. We could obtain a separated object from background when the proposed method was applied to real stereo cameras system.