• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.383-389
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• 2000

This paper presents a stereo camera system that provides a Pair of stereo images using a Biprism. The equivalent of a stereo Pair of images is formed as the left and right halves of a single CCD image. The system is therefore cheap and extremely easy to calibrate since it requires only one CCD camera. An additional advantage of the geometrical set-up is that corresponding features lie on the same scanline automatically, The single camera and Biprism have led to a simple stereo system for which correspondence is very easy and which is accurate for nearby objects in a small field of view. Since we use only a single lens, calibration of the system is greatly simplified. Given the parameters in the Biprism-stereo camera system, we can reconstruct the 3-D structure using only the disparity between the corresponding points.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1843-1844
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• 2008

In this paper, the distance from the camera to the object is measured by using stereo camera. The stereo camera acquires two images which have a disparity from left and right camera. The disparity could be calculated by stereo matching of two images and using the disparity, the distance was calculated by triangular method. The distance estimation was carried out as widen the distance from the camera to the object with several operation methods of stereo matching. The result of experiment was under 10 percent error compared with the real distance. Therefore, by using this result, stereo camera would be adapt to the object tracking robot research or any other related area.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.397-404
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• 2011

This paper proposes an algorithm capable of extracting corresponding points between a pair of stereo images based on dynamic programming. The purpose of extracting the corresponding points is to provide the stereo disparity data to a road-slope estimation algorithm with high accuracy and in real-time. As the road-slope estimation algorithm does not require dense disparity data, the proposed stereo matching algorithm aims at extracting corresponding points accurately and quickly. In order to realize this contradictory goal, this paper exploits dynamic programming, and minimizes matching candidates using vertical components of color edges. Furthermore, the typical occlusion problem in stereo vision is solved. The proposed algorithm is proven to be effective through experiments with various images captured on the roads.

• Journal of the Semiconductor & Display Technology
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• v.15 no.1
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• pp.47-51
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• 2016

Human visual system infers 3D vision through stereo disparity in the stereoscopic images, and stereo visioning are recently being used in consumer electronics which has resulted in much research in the application field. Basically, stereo vision system consists of four processes, which are cost computation, cost aggregation, disparity calculation, and disparity refinement. In this paper, we present and evaluate the existing various methods, focusing on cost aggregation for stereo vision system to comparatively analyze the performance of their algorithms for a given set of resources. Experiments show that Normalized Cross Correlation and Zero-Mean Normalized Cross Correlation provide higher accuracy, however they are computationally heavy for embedded system in the real time systems. Sum of Absolute Difference and Sum of Squared Difference are more suitable selection for embedded system, but they should be required on improvement to apply to the real world system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.424-432
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• 2003

In this paper, an effective method of stereo image reconstruction through the regularized adaptive disparity estimation is proposed. Althougth the conventional adaptive disparity estimation method can sharply improve the PSNR of a reconstructed stereo image, but some problems of overlapping between the matching windows and disallocation of the matching windows can be occurred, because the matching window size changes adaptively in accordance with the magnitude of feature values. Accordingly, in thia paper, a new regularized adaptive disparity estimation technique is proposed. That is, by regularizing the estimated disparity vector with the neughboring disparity vectors, problems of the conventional adaptive disparity estimated scheme might be solved, and also the predicted stereo image can be more effectively reconstructed. From some experiments using the CCETT'S stereo image pairs of 'Man' and 'Claude', it is analyzed that the proposed disparity estimation scheme can improve PSNRs of the reconstructed images to 10.89dB, 6.13dB for 'Man' and 1.41dB, 0.81dB for 'Claude' by comparing with those of the conventional pixel-based and adaptive estimation method, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.735-739
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• 2005

This paper presents a new system to estimate the head pose of human in interactive indoor environment that has dynamic illumination change and large working space. The main idea of this system is to suggest a new morphological feature for estimating head angle from stereo disparity map. When a disparity map is obtained from stereo camera, the matching confidence value can be derived by measurements of correlation of the stereo images. Applying a threshold to the confidence value, we also obtain the specific morphology of the disparity map. Therefore, we can obtain the morphological shape of disparity map. Through the analysis of this morphological property, the head pose can be estimated. It is simple and fast algorithm in comparison with other algorithm which apply facial template, 2D, 3D models and optical flow method. Our system can automatically segment and estimate head pose in a wide range of head motion without manual initialization like other optical flow system. As the result of experiments, we obtained the reliable head orientation data under the real-time performance.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.63-68
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• 2010

In this paper, we propose a multiresolution stereo matching method based on genetic algorithm using edge information. The proposed approach considers the matching environment as an optimization problem and finds the solution by using a genetic algorithm. A cost function composes of certain constraints which are commonly used in stereo matching. We defines the structure of chromosomes using edge pixel information of reference image of stereo pair. To increase the efficiency of process, we apply image pyramid method to stereo matching and calculate the initial disparity map at the coarsest resolution. Then initial disparity map is propagated to the next finer resolution, interpolated and performed disparity refinement. We valid our approach not only reduce the search time for correspondence but alse ensure the validity of matching.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.517-526
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• 2008

Stereo vision is a fundamental method for measuring 3D structures by observing them from two cameras placed on different positions. In order to reconstruct 3D structures, it is necessary to create a disparity map from a pair of stereo images. To create a disparity map we compute the matching cost for each point correspondence and compute the disparity that minimizes the sum of the whole matching costs. In this paper, we propose a method to estimate a dense disparity map using region segmentation. We segment each scanline using region homogeneity properties. Using the segmented regions, we prohibit false matches in the stereo matching process. Disparities for pixels that failed in matching are filled by interpolating neighborhood disparities. We applied the proposed method to various stereo images of real environments. Experimental results showed that the proposed method is stable and potentially viable in practical applications.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.836-838
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• 1999

This paper describes stereo image compression algorithm using disparity and JPEG. because similar images are images with common features, similiar pixel distributions, and similar edge distributions. Fields such as medical imaging or satellite imaging often need to store large collections of similar images. that is, a conventional stereo system with a single left-right pair needs twice data as a monoscopic imaging system. as a result we need compression method compatible stereo image, in this paper after we use JPEG in basic compression method and stereo matching using adaptiv window, we get disparity information, we restored right image using by restored left image and disparity.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.330-334
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• 2001

This paper presents the way of building an occupancy grid map which a mobile robot needs to autonomously navigate in the unknown environment. A disparity map resulting from stereo matching can be converted into the 2D distance information. If the stereo matching has some errors, however, the subsequent map becomes unreliable. In this paper, a new morphological filter is proposed to reject 'spikes' of the disparity map due to stereo mismatch by considering the fact that these spikes occur locally. The new method has advantages that it is simpler and more easily realized than existing similar algorithms.