• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.229-242
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• 2005

Photogrammetry is a current method of GIS data acquisition. However, as a matter of fact, a large manpower and expenditure for making detailed 3D spatial information is required especially in urban areas where various buildings exist. There are no photogrammetric systems which can automate a process of spatial information acquisition completely. On the other hand, LiDAR has high potential of automating 3D spatial data acquisition because it can directly measure 3D coordinates of objects, but it is rather difficult to recognize the object with only LiDAR data, for its low resolution at this moment. With this background, we believe that it is very advantageous to integrate LiDAR data and stereo CCD images for more efficient and automated acquisition of the 3D spatial data with higher resolution. In this research, the automatic urban object recognition methodology was proposed by integrating ultra highresolution stereo images and LiDAR data. Moreover, a method to enable more reliable and detailed stereo matching method for CCD images was examined by using LiDAR data as an initial 3D data to determine the search range and to detect possibility of occlusions. Finally, intellectual DSMs, which were identified urban features with high resolution, were generated with high speed processing.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.181.2-181
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• 2001

Stereo PACS (Picture Archiving and Communication System) is not available yet because of some limitations of medical stereo image software and viewing devices. As a stereo PACS viewer, we designed two functions. One is selecting and viewing a multiplexed stereo image directly, and the other is selecting a stereo pair image (left and right sides both) and merging the stereo pair image into a multiplexed image in software. For the medical image compression of 3-D stereo endoscopic images, we used JPEG and Wavelet compression and to determine an acceptable compression rate using PSNR (Peak Signal-to-Noise Ratio). As a result, we got the conclusion that medically acceptable image compression rate should have the PSNR of above about 40[dB] (JPEG (5:1), Wavelet (10:1)).

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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• pp.143-150
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• 2008

In this paper, we investigate a real-time environment recognition system based on stereo vision for moving object. This system consists of stereo matching, obstacle detection and distance estimation. In stereo matching part, depth maps can be obtained real road images captured adjustable baseline stereo vision system using belief propagation(BP) algorithm. In detection part, various obstacles are detected using only depth map in case of both v-disparity and column detection method under the real road environment. Finally in estimation part, asymmetric parabola fitting with NCC method improves estimation of obstacle detection. This stereo vision system can be applied to many applications such as unmanned vehicle and robot.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.113-122
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• 2012

This paper presents a new stereo matching technique which is based on the matching of feature windows and feature links. The proposed method uses the FAST feature detector to find image features in stereo images and determines the correspondences of the detected features in the stereo images. We define a feature window which is an image region containing several image features. The proposed technique consists of two matching steps. First, a feature window is defined in a standard image and its correspondence is found in a reference image. Second, the corresponding features between the matched windows are determined by using the feature link technique. If there is no correspondence for an image feature in the standard image, it's disparity is interpolated by neighboring feature sets. We evaluate the accuracy of the proposed technique by comparing our results with the ground truth of in a stereo image database. We also compare the matching accuracy and computation time with two conventional feature-based stereo matching techniques.

• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.65-76
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• 2003

The analysis of cow body parameters is important to provide some useful information fur cow management and cow evaluation. Present methods give many stresses to cows because they are invasive and constrain cow postures during measurement of body parameters. This study was conducted to develop the stereo vision system fur non-invasive analysis of cow body features. Body feature parameters of 16 heads at two farms(A, B) were measured using scales and nineteen stereo images of them with walking postures were captured under outdoor illumination. In this study, the camera calibration and inverse perspective transformation technique was established fer the stereo vision system. Two calibration results were presented for farm A and fm B, respectively because setup distances from camera to cow were 510 cm at farm A and 630cm at farm B. Calibration error values fer the stereo vision system were within 2 cm for farm A and less than 4.9 cm for farm B. Eleven feature points of cow body were extracted on stereo images interactively and five assistant points were determined by computer program. 3D world coordinates for these 15 points were calculated by computer program and also used for calculation of cow body parameters such as withers height. pelvic arch height. body length. slope body length. chest depth and chest width. Measured errors for body parameters were less than 10% for most cows. For a few cow. measured errors for slope body length and chest width were more than 10% due to searching errors fer their feature points at inside-body positions. Equation for chest girth estimated by chest depth and chest width was presented. Maximum of estimated error fur chest girth was within 10% of real values and mean value of estimated error was 8.2cm. The analysis of cow body parameters using stereo vision system were successful although body shape on the binocular stereo image was distorted due to cow movements.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.12
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• pp.99-107
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• 1998

A stereo vision system such as the structure of human's eyes has two cameras at separated positions from which we can obtain two input images and then put them together to create 3-D image. It can show more virtual effect than the conventional 2-D image system. But, the stereo image system has to control the convergence angle so that the stereo disparity could always be zero because observers can be fatigued and unconscious of stereo image in conditions that the stereo disparity is not zero for a long work. Therefore, in the paper, optical JTC system which can process adaptive tracking of a specific moving object is proposed as a new approach to keep the stereo disparity to be zero. In this method, optical JTC system obtains the values of the relative locations of a moving objects in left and right images and then these values are used for maintaining the stereo disparity to be zero. Through some optical experiments the proposed stereo vision system is proved to be insensitive to background noises and operate in real-time.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.49-56
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• 2009

Recently, a generation of high quality mosaic images from video sequences has been attempted by a variety of investigations. Among the matter of investigation, in this paper, generation on stereo mosaic utilizing airborne-video sequence images is focused upon. The stereo mosaic is made by creating left and right mosaic which are fabricated by front and rear slices having different viewing angle in consecutive video frames. For making the stereo mosaic, motion parameters which are able to define geometric relationship between consecutive video frames are determined. For determining motion parameters, affine model which is able to explain relative motion parameters is applied by this paper. The mosaicing method using relative motion parameters is called by free mosaic. The free mosaic proposed in this paper consists of 4 step processes: image registration with reference to first frame using affine model, front and rear slicing, stitching line definition and image mosaicing. As the result of experiment, the left and right mosaic image, anaglyphic image for stereo mosaic images are showed and analyzed y-parallax for checking accuracy.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.145-154
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• 2009

For developing an Automation equipment in construction, it is a key issue to develop 3D modeling technology which can be used for automatically recognizing environmental objects. Recently, for the development of "Intelligent Excavating System(IES), a research developing the real-time 3D terrain modeling technology has been implemented from 2006 in Korea and a stereo vision system is selected as the optimum technology. However, as a result of performance tests implemented in various earth moving environment, the 3D images obtained by stereo vision included considerable noise. Therefore, in this study, for getting rid of the noise which is necessarily generated in stereo image matching, the noise elimination algorithm of stereo-vision images for 3D terrain modeling was developed. The consequence of this study is expected to be applicable in developing an automation equipments which are used in field environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.326-331
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• 2019

In the real world, there are both dynamic objects and static objects, but an autonomous vehicle or mobile robot cannot distinguish between them, even though a human can distinguish them easily. It is important to distinguish static objects from dynamic objects clearly to perform autonomous driving successfully and stably for an autonomous vehicle or mobile robot. To do this, various sensor systems can be used, like cameras and LiDAR. Stereo camera images are used often for autonomous driving. The stereo camera images can be used in object recognition areas like object segmentation, classification, and tracking, as well as navigation areas like 3D world reconstruction. This study suggests a method to distinguish static/dynamic objects using stereo vision for an online autonomous vehicle and mobile robot. The method was applied to a 3D world map reconstructed from stereo vision for navigation and had 99.81% accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.325-331
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• 2015

This paper suggests an intersection method to improve the accuracy of three-dimensional position from heterogeneous satellite stereo images, and addresses validation of the suggested method following the experimental results. The three-dimensional position is achieved by determining an intersection point of two rays that have been precisely adjusted through the sensor orientation. In case of conventional homogeneous satellite stereo images, the intersection point is generally determined as a mid-point of the shortest line that links two rays in at least square fashion. In this paper, a refined method, which determines the intersection point upon the ray adjusted at the higher resolution image, was used to improve the positioning accuracy of heterogeneous satellite images. Those heterogeneous satellite stereo pairs were constituted using two KOMPSAT-2 and QuickBird images of covering the same area. Also, the positioning results were visually compared in between the conventional intersection and the refined intersection, while the quantitative analysis was performed. The results demonstrated that the potential of refined intersection improved the positioning accuracy of heterogeneous satellite stereo pairs; especially, with a weak geometry of the heterogeneous satellite stereo, the greater effects on the accuracy improvement.