• Proceedings of the IEEK Conference
• /
• 2000.06d
• /
• pp.210-213
• /
• 2000

In the closed range space, the parallel two CCD cameras are used to acquire a pair of stereo image. The acquired stereo image are computed with Wavelet Transform repeatedly and including the low frequency component, the image size of those are reduced. It is the pyramid structure. The optimum matching point is searched to the pixel. Then appling the optimum matching point to DLT, it extract the three - dimensional surface coordinate from a stereo image. The direct linear transformation(DLT) method is used to calibrate the stereo camera compute the coordinate on a three dimensional space. To find the parameters for the DLT method, 30 control points which marked on the cylinder type object are used. To improve the matching algorithm, the paper select the pyramid structure for Wavelet Transform. The acquired disparity information is used to represent the really three-dimensional surface coordinate.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.1
• /
• pp.224-241
• /
• 2015

Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.55 no.2
• /
• pp.103-109
• /
• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a intelligent path planning of an automatic mobile robot is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity mad obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene. and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation.

• Journal of Ocean Engineering and Technology
• /
• v.15 no.1
• /
• pp.79-84
• /
• 2001

This paper present the control of the image disparity of a parallel stereo camera and its application to an underwater stereo camera to enhance the working efficiency of underwater vehicles that are equiped with manipulators in seabed operation. The stereo camera consists of two parallel lenses mounted on a lateral moving base and two CCD cameras mounted on a longitudinal moving base, which is embedded in a small pressure canister for underwater application. Because the lateral shift is related to the backward shift with a nonlinear relation, only one control input is needed to control the vergence and focus of the camera with a special driving device. We can get clear stereo vision with the camera for all the range of objects in air and in water, especially in short range object. The control system of the camera is so simple that we are able to realize a small stereo camera system and apply it to a stereo vision system for underwater vehicles. This paper also shows how to acquire the distance information of an underwater object with this stereo camera. Whenever we focus on an underwater object with the camera, we can obtain three-dimensional images and distance information in real-time.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.9
• /
• pp.1613-1631
• /
• 2011

Several metrics have been reported in the literature to assess stereo image quality, mostly based on visual attention or human visual sensitivity based distortion prediction with the help of disparity information, which do not consider the combined aspects of human visual processing. In this paper, visual attention and depth assisted stereo image quality assessment model (VAD-SIQAM) is devised that consists of three main components, i.e., stereo attention predictor (SAP), depth variation (DV), and stereo distortion predictor (SDP). Visual attention is modeled based on entropy and inverse contrast to detect regions or objects of interest/attention. Depth variation is fused into the attention probability to account for the amount of changed depth in distorted stereo images. Finally, the stereo distortion predictor is designed by integrating distortion probability, which is based on low-level human visual system (HVS), responses into actual attention probabilities. The results show that regions of attention are detected among the visually significant distortions in the stereo image pair. Drawbacks of human visual sensitivity based picture quality metrics are alleviated by integrating visual attention and depth information. We also show that positive correlation with ground-truth attention and depth maps are increased by up to 0.949 and 0.936 in terms of the Pearson and the Spearman correlation coefficients, respectively.

• Journal of Korea Multimedia Society
• /
• v.16 no.6
• /
• pp.764-781
• /
• 2013

In this paper, we propose a highly precise vehicle detection method with low false alarm using billboard sweep stereo matching and multi-stage hypothesis generation. First, we capture stereo images from cameras established in front of the vehicle and obtain the disparity map in which the regions of ground plane or background are removed using billboard sweep stereo matching algorithm. And then, we perform the vehicle detection and tracking on the labeled disparity map. The vehicle detection and tracking consists of three steps. In the learning step, the SVM(support vector machine) classifier is obtained using the features extracted from the gabor filter. The second step is the vehicle detection which performs the sobel edge detection in the image of the left camera and extracts candidates of the vehicle using edge image and billboard sweep stereo disparity map. The final step is the vehicle tracking using template matching in the next frame. Removal process of the tracking regions improves the system performance in the candidate region of the vehicle on the succeeding frames.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.12 no.2
• /
• pp.127-138
• /
• 2012

In this paper, we propose a real-time virtual re-convergence hardware platform especially to reduce the visual fatigue caused by stereoscopy. Our unique idea to reduce visual fatigue is to utilize the virtual re-convergence based on the optimized disparity-map that contains more depth information in the negative disparity area than in the positive area. Our virtual re-convergence hardware platform, which consists of image rectification, disparity estimation, depth post-processing, and virtual view control, is realized in real time with 60 fps on a single Xilinx Virtex-5 FPGA chip.

• Proceedings of the Korea Contents Association Conference
• /
• 2011.05a
• /
• pp.499-500
• /
• 2011

Line Disparity Map[1]은 스테레오 영역기반 정합방법에서 블록단위의 영역이 아닌 라인의 기울기를 바탕으로 비교하기 때문에 실시간 스테레오 정합이 가능하다. 따라서 본 논문은 이러한 Line Disparity Map 알고리즘을 사용하여 단순히 관찰로만 사용되어 지는 입체현미경에 스테레오 비전을 기반으로 하는 3D 형상계측 시스템을 개발하여 사람이 손으로 측정하기 힘든 미세의 오브젝트를 측정하는 시스템을 개발하고자 한다.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.7
• /
• pp.78-84
• /
• 2016

This paper presents and implements a vehicle speed measurement system using a license plate recognition system and a stereo camera. Using the feature points of the license plate recognition system, the disparity information is extracted and then the distance to the feature points is calculated by using the disparity information. In this paper, a vehicle speed is measured using the adjacent distances from consecutive stereo images and the corresponding time of the distances. Actual vehicle speed is also measured using the reference measurement equipment (tape switch based system) in order to test the accuracy of the proposed speed measurement system. The implemented stereo based speed measurement system shows appropriate result within specification both in the daytime and nighttime experiments.

• Journal of IKEEE
• /
• v.26 no.4
• /
• pp.686-692
• /
• 2022

In this paper, the matching error rates of modified area-based, energy-based algorithms, and learning-based structures were compared for stereo image matching. Census transform (CT) based on region and life propagation (BP) algorithm based on energy were selected, respectively.Existing algorithms have been improved and implemented in an embedded processor environment so that they can be used for stereo image matching in mobile systems. Even in the case of the learning base to be compared, a neural network structure that utilizes small-scale parameters was adopted. To compare the error rates of the three matching methods, Middlebury's Tsukuba was selected as a test image and subdivided into non-occlusion, discontinuous, and disparity error rates for accurate comparison. As a result of the experiment, the error rate of modified CT matching improved by about 11% when compared with the existing algorithm. BP matching was about 87% better than conventional CT in the error rate. Compared to the learning base using neural networks, BP matching was about 31% superior.