• 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.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.171-182
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• 2015

We propose a camera system to acquire indoor stereo omni-directional images and its calibration method. These images can be utilized for indoor precise mapping and sophisticated imagebased services. The proposed system is configured with a rotating stereo line camera system, providing stereo omni-directional images appropriate to stable stereoscopy and precise derivation of object point coordinates. Based on the projection model, we derive a mathematical model for the system calibration. After performing the system calibration, we can estimate object points with an accuracy of less than ${\pm}16cm$ in indoor space. The proposed system and calibration method will be applied to indoor precise 3D modeling.

• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.669-679
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• 2013

This paper proposed a new VLSI (Very Large Scale Integrated Circuit) architecture for stereo matching in real time. We minimized the amount of calculation and the number of memory accesses through analyzing calculation of stereo matching. From this, we proposed a new stereo matching calculating cell and a new hardware architecture by expanding it in parallel, which concurrently calculates cost function for all pixels in a search range. After expanding it, we proposed a new hardware architecture to calculate cost function for 2-dimensional region. The implemented hardware can be operated with minimum 250Mhz clock frequence in FPGA (Field Programmable Gate Array) environment, and has the performance of 805fps in case of the search range of 64 pixels and the image size of $640{\times}480$.

• Journal of Ubiquitous Convergence Technology
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• v.1 no.1
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• pp.9-17
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• 2007

Feature based stereo matching is an effective way to perform 3D building reconstruction. However, in urban scene, the cluttered background and various building structures may interfere with the performance of building reconstruction. In this paper, we propose a novel method to robustly reconstruct buildings on the basis of rectangle regions. Firstly, we propose a multi-scale linear feature detector to obtain the salient line segments on the object contours. Secondly, candidate rectangle regions are extracted from the salient line segments based on their local information. Thirdly, stereo matching is performed with the list of matching line segments, which are boundary edges of the corresponding rectangles from the left and right image. Experimental results demonstrate that the proposed method can achieve better accuracy on the reconstructed result than pixel-level stereo matching.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.602-608
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• 2015

This paper proposes an algorithm for precise detection of corner points on a coplanar checkerboard in order to perform stereo camera calibration using a single frame. Considering the conditions of automobile production lines where a stereo camera is attached to the windshield of a vehicle, this research focuses on a coplanar calibration methodology. To obtain the accurate values of the stereo camera parameters using the calibration methodology, precise localization of a large number of feature points on a calibration target image should be ensured. To realize this demand, the idea with respect to a checkerboard pattern design and the use of a Homography matrix are provided. The calibration result obtained by the proposed method is also verified by comparing the depth information from stereo matching and a laser scanner.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.519-524
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• 2009

This paper describes a new sensor system for 3D environment perception using stereo structured infrared light sources and a camera. Environment and obstacle sensing is the key issue for mobile robot localization and navigation. Laser scanners and infrared scanners cover $180^{\circ}$ and are accurate but too expensive. Those sensors use rotating light beams so that the range measurements are constrained on a plane. 3D measurements are much more useful in many ways for obstacle detection, map building and localization. Stereo vision is very common way of getting the depth information of 3D environment. However, it requires that the correspondence should be clearly identified and it also heavily depends on the light condition of the environment. Instead of using stereo camera, monocular camera and two projected infrared light sources are used in order to reduce the effects of the ambient light while getting 3D depth map. Modeling of the projected light pattern enabled precise estimation of the range. Two successive captures of the image with left and right infrared light projection provide several benefits, which include wider area of depth measurement, higher spatial resolution and the visibility perception.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2251-2259
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• 2009

We propose an algorithm and system which generates 3D stereo image by composition of 2D image from 4 multiple clusters which 1 cluster was composed of 4 multiple cameras based on network. Proposed Schemes have a network-based client-server architecture for load balancing of system caused to process a large amounts of data with real-time as well as multiple cluster environments. In addition, we make use of JPEG compression and RAM disk method for better performance. Our scheme first converts input images from 4 channel, 16 cameras to binary image. And then we generate 3D stereo images after applying edge detection algorithm such as Sobel algorithm and Prewiit algorithm used to get disparities from images of 16 multiple cameras. With respect of performance results, the proposed scheme takes about 0.05 sec. to transfer image from client to server as well as 0.84 to generate 3D stereo images after composing 2D images from 16 multiple cameras. We finally confirm that our scheme is efficient to generate 3D stereo images in multiple view and multiple clusters environments with real-time.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.216-224
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• 1997

In this paper, we propose a depth information extraction method for intermediate image synthesis. As stereo matching method, MBS(Multiple-Baseline Stereo) method has been proposed, in which the matching accuracy increases by using the multiple camera, but there are some inherent problems such as computational complexity, boundary overreach(BO) in depth map, and occlusion. So, we propose the modified version of MBS so called Multi-Resolution MBS(MR-MBS). Moreover, we also propose an adaptive occlusion area processing technique to improve the accuracy of the depth information in occlusion area.

• Journal of Broadcast Engineering
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• v.10 no.1 s.26
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• pp.68-76
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• 2005

We propose a new type of stereoscopic camera system with a zoom lens module to overcome the backlash for the stability of picture matching and the difficulty of zoom control. This system is designed to control a pair of zoom lens with a rotation lever. In this paper, we present the structural characteristics of our proposed system, and verify that there are no image mismatching at acquired stereo images and the zoom in$\cdot$out is easy to control. In our experiments, we achieve good results that a convergence control is very simple and distortion of images is decreased.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1518-1525
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• 2021

Due to the growth of VR industry and rise of digital twin industry, the importance of implementing 3D data same as real space is increasing. However, the fact that it requires expertise personnel and huge amount of time is a problem. In this paper, we propose a system that generates point cloud data with same shape and color as a real space, just by scanning the space. The proposed system integrates 3D geometric information from lidar and color information from stereo camera into one point cloud. Since the number of 3D points generated by lidar is not enough to express a real space with good quality, some of the pixels of 2D image generated by camera are mapped to the correct 3D coordinate to increase the number of points. Additionally, to minimize the capacity, overlapping points are filtered out so that only one point exists in the same 3D coordinates. Finally, 6DoF pose information generated from lidar point cloud is replaced with the one generated from camera image to position the points to a more accurate place. Experimental results show that the proposed system easily and quickly generates point clouds very similar to the scanned space.