• Journal of Korean Ophthalmic Optics Society
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• v.12 no.1
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• pp.53-59
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• 2007

A commonly used device to determine fixation disparity curves is the Wesson Fixation Disparity Card. A fixation disparity curve is an x, y coordinate plot of the angular amount of fixation disparity as a function of the power of prisms through which the patient views. The fixation disparity curve variables that are used to aid in the diagnosis and management of binocular vision disorders include the x-intercept, y-intercept, curve slope and curve type. Fixation disparity curves were measured on 102 subjects with the Wesson fixation disparity card. The purpose of this study is to investigate distribution of the curve types obtained with Wesson card. Fixation Disparity by Wesson Fixation Disparity Card were that in case of type I 63.0%, in case of type II 0.0%, in case of type III 25.0% and in case of type IV 12.0%.

• Journal of Korean Ophthalmic Optics Society
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• v.15 no.1
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• pp.61-66
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• 2010

Purpose: This study was performed to determine vertical fixation disparity by Fixation Disparity Card. The purpose of this study was to investigate distribution of the curve types obtained with Wesson card. Methods: Fixation disparity curves were measured on 52 subjects with the Wesson fixation disparity card. A fixation disparity curve was an x, y coordinate plot of the angular amount of fixation disparity as a function of the power of prisms through which the patient views. The fixation disparity curve variables that were used to aid in the diagnosis and management of binocular vision disorders included the x-intercept, y-intercept, curve slope and curve type. Results: Vertical fixation disparity curves by Wesson Fixation Disparity Card were very various. Conclusions: Vertiical fixation disparity curves could be used to aid in the diagnosis and prescription.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.279-287
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• 2009

In this paper, a hierarchical stereo matching with color information is proposed. To generate an initial disparity map, feature based stereo matching is carried out and to generate a final disparity map, hierarchical stereo matching is carried out. The boundary (edge) region is obtained by segmenting a given image into R, G, B and White components. From the obtained boundary, disparity is extracted. The initial disparity map is generated when the extracted disparity is spread to the surrounding regions by evaluating autocorrelation from each color region. The initial disparity map is used as an initial value for generating the final disparity map. The final disparity map is generated from each color region by changing the size of a block and the search range. 4 test images that are provided by Middlebury stereo vision are used to evaluate the performance of the proposed algorithm objectively. The experiment results show better performance compared to the Graph-cuts and Dynamic Programming methods. In the final disparity map, about 11% of the disparities for the entire image were inaccurate. It was verified that the boundary for the non-contiguous point was clear in the disparity map.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.7
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• pp.37-42
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• 2008

In this paper, a real-time multiview video coding system using fast disparity estimation is proposed. In the multiview encoder, adaptive disparity-motion estimation (DME) for an effective 3-dimensional (3D) processing are proposed. That is, by adaptively predicting the mutual correlation between stereo images in the key-frame using the proposed algorithm, the bandwidth of stereo input images can be compressed to the level of a conventional 2D image and a predicted image also can be effectively reconstructed using a reference image and adaptive disparity vectors. Also, in multiview decoder, intermediate view reconstruction (IVR) using adaptive disparity search algorithm (DSA) for real-time multiview video processing is proposed. The proposed IVR can reduce a processing time of disparity estimation by selecting adaptively disparity search range. Accordingly, the proposed multiview video coding system is able to increase the efficiency of the coding rate and improve the resolution.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4375-4388
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• 2018

To solve the problem of transmission errors in stereoscopic images, this paper proposes a novel error concealment (EC) method using superpixel segmentation and adaptive disparity selection (SSADS). Our algorithm consists of two steps. The first step is disparity estimation for each pixel in a reference image. In this step, the numbers of superpixel segmentation labels of stereoscopic images are used as a new constraint for disparity matching to reduce the effect of mismatching. The second step is disparity selection for a lost block. In this step, a strategy based on boundary smoothness is proposed to adaptively select the optimal disparity which is used for error concealment. Experimental results demonstrate that compared with other methods, the proposed method has significant advantages in both objective and subjective quality assessment.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.99-102
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• 2009

In this paper a hierarchical stereo matching algorithm based on feature extraction is proposed. The boundary (edge) as feature point in an image is first obtained by segmenting an image into red, green, blue and white regions. With the obtained boundary information, disparities are extracted by matching window on the image boundary, and the initial disparity map is generated when assigned the same disparity to neighbor pixels. The final disparity map is created with the initial disparity. The regions with the same initial disparity are classified into the regions with the same color and we search the disparity again in each region with the same color by changing block size and search range. The experiment results are evaluated on the Middlebury data set and it show that the proposed algorithm performed better than a phase based algorithm in the sense that only about 14% of the disparities for the entire image are inaccurate in the final disparity map. Furthermore, it was verified that the boundary of each region with the same disparity was clearly distinguished.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.298-304
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• 2009

This paper describes an algorithm that improves 3D reconstruction result using a multi-sensor fusion disparity map. We can project LRF (Laser Range Finder) 3D points onto image pixel coordinatesusing extrinsic calibration matrixes of a camera-LRF (${\Phi}$, ${\Delta}$) and a camera calibration matrix (K). The LRF disparity map can be generated by interpolating projected LRF points. In the stereo reconstruction, we can compensate invalid points caused by repeated pattern and textureless region using the LRF disparity map. The result disparity map of compensation process is the multi-sensor fusion disparity map. We can refine the multi-sensor 3D reconstruction based on stereo vision and LRF using the multi-sensor fusion disparity map. The refinement algorithm of multi-sensor based 3D reconstruction is specified in four subsections dealing with virtual LRF stereo image generation, LRF disparity map generation, multi-sensor fusion disparity map generation, and 3D reconstruction process. It has been tested by synchronized stereo image pair and LRF 3D scan data.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.304-309
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• 1999

In this paper, we presents a new disparity map refinement algorithm using statistical characteristics of disparity map and edge information. The proposed algorithm generate a refined disparity map using disparity maps which are obtained from area and feature-based Stereo Matching by selecting a disparity value of edge point based on the statistics of both disparity maps. Experimental results on aerial stereo image show the better results than conventional fusion algorithms in the disparity error. This algorithm can be applied to the reconstruction of building image from the high resolution remote sensing data.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.131-143
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• 1998

This paper presents a high performance disparity extraction algorithm that generate a dense and accurate disparity map using low-resolution disparity histogram. Disparity distribution of background and object areas can besegmented from low-resolution disparity histogram. These information can be used to reduce the search area and search range of the high-resolution image resulting reliable disparity information in high speed. The computationally efficient matching pixel count(MPC) similarity measure technique is useed extensively toremove the redundancies inherent in the area-based matching method, and also results robust matching at the boundary region. Resulting maches are further improved using iterative support algorithm and post processing. We have obtained good results on randomdot stereogram and real images obtained in our carmera system.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.83-92
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• 2006

This paper describes an image disparity estimation method using region-based stereo matching. Region-based disparity estimation yields a disparity map as the unit of segmented region. However it estimates disparity imprecisely because it not only has matching errors but also applies an identical way to disparity estimation, which does not consider each type of matched regions. To solve this problem, we proposes a disparity estimation method which considers the type of matched regions. That is, the proposed method classifies whole matched regions into a similar-matched region, a dissimilar-matched region, a false-matched region and a miss-matched region. We then performs proper disparity estimation for each type of matched regions. This method minimizes the error in estimating disparity which is caused by inaccurate matching and also improves the accuracy of disparity of the well-matched regions. The experimental results show the improved accuracy of the proposed method.