• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2189-2196
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• 2015

Stereo matching algorithm is usually used to obtain a disparity map from a pair of images. However, the disparity map obtained by using stereo matching contains lots of noise and error regions. In this paper, we propose a virtual-view synthesis algorithm using disparity refinement in order to improve the quality of the synthesized image. First, the error region is detected by examining the consistency of the disparity maps. Then, motion information is acquired by applying optical flow to texture component of the image in order to improve the performance. Then, the occlusion region is found using optical flow on the texture component of the image in order to improve the performance of the optical flow. The refined disparity map is finally used for the synthesis of the virtual view image. The experimental results show that the proposed algorithm improves the quality of the generated virtual-view.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.65-72
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• 2000

In this paper we propose the new binary image matching algorithm called the Fuzzy logic induced Hausdorff Distance(FHD) for finding the maximally matched image with the query image. The membership histogram is obtained by normalizing the cardinality of the subset with the corresponding radius after obtaining the distribution of the minimum distance computed by the Hausdroff distance between two binary images. in the proposed algorithm, The fuzzy influence method Center of Gravity(COG) is applied to calculate the best matching candidate in the membership function described above. The proposed algorithm shows the excellent results for the face image recognition when the noise is added to the query image as well as for the character recognition.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.733-736
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• 1998

In this paper, we propose a new method for content-based retrieval system using wavelet transform and correlation, which has were used in signal processing and image compressing. The matching method is used not perfect matching but similar matching. Used feature vector is the lowest frequency(LL) itself, energy value, and edge information of 4-layer, after computng a 4-layer 2-D fast wavelet transform on image. By the proosed algorithm, we got the result that was faste rand more accurate than the traditional algorithm. Because used feature vector was compressed 256:1 over original image, retrieval speed was highly improved. By using correlation, moving object with size variation was reterieved without additional feature information.

• 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.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.126-128
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• 2006

For pattern matching, an object image should be segmented and analyzed for the first time. Thresholding is a fundamental approach to segmentation that utilizes a significant degree of pixel popularity or intensity. Otsu's thresholding is one of the most veil-known methods proposed in the literature. However, the method has a disadvantage of repeatedly searching the optimal thresholds for the entire region. To overcome this problem, a number of methods have been proposed. In this paper, we propose a simple and fast thresholding method of finding multi-level threshold values by extending the Otsu's method. Our experimental results for the benchmak images show a possibility that the proposed method could be used efficiently for pattern matching.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.228-233
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• 1997

An efficient corner matching algorithm is developed to minimize the amount of calculation. To reduce the amount of calculation, all available information from a corner detector is used to make model. This information has uncertainties due to discretization noise and geometric distortion, and this is represented by fuzzy rule base which can represent and handle the uncertainties. Form fuzzy inference procedure, a matched segment list is extracted, and resulted segment list is used to calculate the transformation between object of model and scene. To reduce the false hypotheses, a vote and re-vote method is developed. Also an auto tuning scheme of the fuzzy rule base is developed to find out the uncertainties of features from recognized results automatically. To show the effectiveness of the developed algorithm, experiments are conducted for images of real electronic components.

• ETRI Journal
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• v.28 no.2
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• pp.162-174
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• 2006

Several photogrammetric and geographic information system applications such as surface matching, object recognition, city modeling, environmental monitoring, and change detection deal with multiple versions of the same surface that have been derived from different sources and/or at different times. Surface registration is a necessary procedure prior to the manipulation of these 3D datasets. This need is also applicable in the field of medical imaging, where imaging modalities such as magnetic resonance imaging (MRI) can provide temporal 3D imagery for monitoring disease progression. This paper will present a general automated surface registration procedure that can establish correspondences between conjugate surface elements. Experimental results using light detection and ranging (LIDAR) and MRI data will verify the feasibility, robustness, and accuracy of this approach.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2228-2230
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• 1998

This paper presents the development of depth extraction algorithm for the stereoscopic endoscope data using a stereo matching method. generally, the purpose of existing stereo algorithms is to reconstruct stereo object surface and depth map. but the main purpose of our processing is to give exact depth feeling to doctor showing depth information in some points. for this purpose, this paper presents two stereo matching algorithms which are to measure exact depth. one is using variable window, and the other is reference points-based algorithm for a fast processing.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.559-566
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• 2005

An effective do-blurring algorithm is proposed to remove the blur of the even and the odd line images of the interlaced scan type camera. n the object or the camera moves fast while the interlaced scan type digital camera is acquiring images, blur is often created due to the misalignment between two images of even and odd lines. In this paper, the blurred original image is separated into the even and the odd line images of the half size. Two full sized images are generated using interpolation technique based on these two in ages. Again, these images are signed and combined through the processes of feature extraction, matching, sub-pixel matching, outlier removal, and mosaicking. De-blurring simulations about the images of different camera motions have been done.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.3
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• pp.349-354
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• 2011

In this paper we propose a simple efficient stereo matching algorithm to recover sharp object boundaries and to obtain dense disparity map using new multiple line shape windows. To this end, we consider left-right consistency and unique constraint. From the experimental results it is found that the proposed algorithm is very good for obtaining sharp and dense disparity maps for stereo image pairs.