• Journal of Biomedical Engineering Research
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• v.22 no.6
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• pp.527-534
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• 2001

Conventional stereo image acquisition uses a pair of frame grabbers in the CAS(Computer Assisted Surgery) system. In this Paper, we developed a synchronized stereo image acquisition method with only one frame grabber Two images from left and right camera each other. were merged with different color space without time delay and thus only one frame grabber was enough toy stereo image. Due to this synchronous Property of image acquisition, we can improve spatial revolution on the computation of 3D Position. Furthermore the overall costs for 3D navigator can be down and the extraction time of stereo Position tan be shortened.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.155-164
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• 2001

In this study, we describe the technique for deriving a digital elevation model (DEM) from a synthetic aperture radar (SAR) stereo image pair and apply it to an image pair over "Kwanak-san" in Seoul, Korea. This paper contains brief discussion of the use of stereo SAR to derive topographic data, description of the overall structure of the stereo SAR processing system, description of the site and SAR data used for the evaluation and the source of validation data, results of the stereo SAR processing, analysis and evaluation of their accuracy against map data, and finally summarizes the main highlights of the method used, comments and recommendations on its future implementation.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.135-143
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• 2005

RPC(Rational Polynomial Camera) models have become the replacement model of choice for a number of high resolution satellite imagery providers. RPCs(Rational Polynomial Coefficients) provide a compact accurate representation of the ground to image geometry, allowing users to perform full photogrammetric processing of satellite imagery including block adjustment, 3D feature extraction and orthorectification. This paper presents an algorithm for 3D feature extraction using downhill simpler method which requires only function evaluations, not derivatives. The algorithm was implemented as an executable software program and tested using stereo IKONOS images of Seoul city. The results showed that the proposed algorithm was fast and accurate enough to be used as a practical method for the 3D feature extraction from stereo images with RPCs.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2000.10a
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• pp.90-95
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• 2000

This paper presents the vergence control of a parallel stereo camera and its application to underwater stereo camera to enhance the working efficiency of underwater vehicles that equips 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 a clear stereo vision with the camera for all the range of objects in air and in water, especially in short range objects. The control system of the camera is so simple that we are able to realize a small stereo camera system and to 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 the three-dimensional images and the distance information in real-time.

• Journal of Information Display
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• v.6 no.4
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• pp.26-34
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• 2005

In this paper, a new rectification scheme to transform the uncalibrated stereo image pair into the calibrated one is suggested and its performance is analyzed by applying this scheme to the reconstruction of the intermediate views for multi-view stereoscopic display. In the proposed method, feature points are extracted from the stereo image pair by detecting the comers and similarities between each pixel of the stereo image pair. These detected feature points, are then used to extract moving vectors between the stereo image pair and the epipolar line. Finally, the input stereo image pair is rectified by matching the extracted epipolar line between the stereo image pair in the horizontal direction. Based on some experiments done on the synthesis of the intermediate views by using the calibrated stereo image pairs through the proposed rectification algorithm and the uncalibrated ones for three kinds of stereo image pairs; 'Man', 'Face' and 'Car', it is found that PSNRs of the intermediate views reconstructed from the calibrated images improved by about 2.5${\sim}$3.26 dB than those of the uncalibrated ones.

• Journal of Ocean Engineering and Technology
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• v.15 no.1
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• pp.79-84
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• 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)
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• v.5 no.9
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• pp.1613-1631
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• 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 the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4807-4813
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• 2012

Since the existing methods of segmenting target objects from various images mainly use 2-dimensional features, they have several constraints due to the shortage of 3-dimensional information. In this paper, we therefore propose a new method of accurately segmenting target objects from three dimensional stereoscopic images using 2D and 3D feature clustering. The suggested method first estimates depth features from stereo images by using a stereo matching technique, which represent the distance between a camera and an object from left and right images. It then eliminates background areas and detects foreground areas, namely, target objects by effectively clustering depth and color features. To verify the performance of the proposed method, we have applied our approach to various stereoscopic images and found that it can accurately detect target objects compared to other existing 2-dimensional methods.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.677-686
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• 2014

This paper analyzes the 3D accuracy of stereo images captured from a mobile phone. For 3D accuracy evaluation, we have compared the accuracy result according to the amount of the convergence angle. In order to calculate the 3D model space coordinate of control points, we perform inner orientation, distortion correction and image geometry estimation. And the quantitative 3D accuracy was evaluated by transforming the 3D model space coordinate into the 3D object space coordinate. The result showed that relatively precise 3D information is generated in more than $17^{\circ}$ convergence angle. Consequently, it is necessary to set up stereo model structure consisting adequate convergence angle as an measurement distance and a baseline distance for accurate 3D information generation. It is expected that the result would be used to stereoscopic 3D contents and 3D reconstruction from images captured by a mobile phone camera.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.53-62
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• 1998

In this paper, a genetic algorithm-based optimization technique for stereo matching is proposed. Stereo matching is an essential process to recover three-dimensional structure of objects. The proposed two-dimensional chromosomes consist fo disparity values. The cost function of each chromosome is composed of the intensity-difference between two images and smoothness of disparity. The crossover and mutation operators in the two-dimensional chromosomes are described. The operations are affected by the disparities of neighbor pixels. The knowledge-augmented operators are shown to result in rapid convergence and stable result. The genetic algorithm for stereo matching is tested on synthetic and natural images. Experimental results of various images show that the proposed algorithm has good performance even if the images have too dense or sparse feature points. severe noise, and repeating pattern.