• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.102-110
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• 2015

In this paper, adaptive matching method using the same features for rigid and deformable object images is proposed. Firstly, we determine whether the two images are matched or not using the geometric verification and generate the matching information. Decision boundary which separates deformable matching-pair from non-matching pair is obtained through statistical analysis of matching information. The experimental result shows that the proposed method lowers the computational complexity and increases the matching accuracy compared to the existing method.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.279-286
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• 2000

The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.

• Journal of Korean Society for Geospatial Information Science
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• v.3 no.2 s.6
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• pp.213-220
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• 1995

Map Matching is the method for correcting the current position from dead reckoning in Car Navigation System. In this paper, we proposed the new map matching algorithm that can correct the positioning error caused by sensors and digital map data around the cross road area. To do this, first we set the error boundary of the cross road area by combining the relative error of moving distance and the absolute error of road length, second, we find out the starting point of turning within the determined error boundary of the cross point area, third, we compare the turning angle of the car to the angle of each possible road, and the last, we decide the matched road. We used wheel sensor as a speed sensor and used optical fiber gyro as a directional sensor, and assembled the sensors to the notebook computer. We testified our algorithm by driving the Daejeon area-which is a part of south Korea-as a test area. And we proved the efficiency by doing that.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1125-1132
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• 2004

In this Paper, we Propose an effective boundary matching based error detection algorithm using causal neighbor blocks to improve video quality degraded from channel error in block-coded video. The proposed algorithm first calculates boundary mismatch powers between a current block and each of its causal neighbor blocks. It then decides that a current block should be normal if all the mismatch powers are less than an adaptive threshold, which is adaptively determined using the statistics of the two adjacent blocks. In some experiments under the environment of 16bi1s burst error at bit error rates (BERs) of 10$^{-3}$ -10$^{-4}$ , it is shown that the proposed algorithm yields the improvements of maximum 20% in error detection rate and of maximum 3.5㏈ in PSNR of concealed kames, compared with Zeng's error detection algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.91-98
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• 2005

In this paper, we propose a temporal error concealment method based on the edge adaptive masking. In the method, four regions around the corrupted block - top, bottom, left, and right - are defined and the edge features of the regions are extracted by applying an edge operator for each direction. The size of a mask for the boundary matching is determined by the edge information, which can be considered as a criterion to measure the activity of the boundary region. In other words, it is determined such that the size of the mask is proportional to the amount of edge-component extracted from each region in order to yield the higher reliability on boundary matching. This process is equivalent to applying weights depending on the edge features, which leads the improved motion vector. In experiments, it is verified that the proposed method outperforms the conventional methods in terms of image quality, and then its merits and demerits are discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.683-691
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• 2004

To transmit MPEG-2 video on an errorneous channel, a number of error control techniques are needed. Especially, error concealment techniques which can be implemented on receivers independent of transmitters are essential to obtain good video quality. In this paper, prediction of motion vector and an adaptive boundary matching algorithm are presented for temporal error concealment. Before the complex BMA, we perform error concealment by a motion vector prediction using neighboring motion vectors. If the candidate of error concealment is not satisfied, search range and reliable boundary pixels are selected by the temporal activity or motion vectors and a damaged macroblock is concealed by applying an adaptive BMA. This error concealment technique reduces the complexity and maintains a PSNR gain of 0.3∼0.7㏈ compared to conventional BMA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11C
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• pp.1049-1058
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• 2009

After the efficiency of H.264 video compression has been announced, it replaced MPEG-2 standard in several applications. So transcoding methods of MPEG-2 to H.264 have been studying because there are variety devices and contents followed by MPEG-2. Although H.264 supported various service such as IPTV, DMB, digital broadcasting etc, but users using MPEG-2 devices cannot accessible to them. This paper propose H.264 to MPEG-2 transcoding for users of MPEG-2 devices without displacement H.264. The proposed method predicted a motion vector for MPEG-2 encoder after it extracted from motion vectors of variable blocks in H.264 to improve processing time. Also it predicted a optimal motion vector using modified boundary matching algorithm after grasped a special character for boundary and background of object. The experimental results from proposed method show a considerable reduction in processing time, as much as 65% averagely, with a small objective quality reduction in PSNR.

• Journal of KIISE:Information Networking
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• v.31 no.3
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• pp.298-304
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• 2004

In transmitting a compressed video bit-stream over Internet, a packet loss causes an error propagation in both spatial and temporal domain, which in turn leads to a severe degradation in image quality. In this paper, a new error concealment algorithm is proposed to repair damaged portions of the video frames in the receiver. Conventional BMA(Boundary Matching Algorithm) assumes that the pixels on the boundary of the missing block and its neighboring blocks are very similar, but has no consideration of edges t)r discontinuity across the boundary. In our approach, the edges are detected across the boundary of the lost or erroneous block. Once the edges are detected and the orientation of each edge is found, only the pixel difference along the expected edges across the boundary is measured instead of calculating differences between all adjacent pixels on the boundary. Therefore, the proposed approach needs very few computations and the experiment shows an improvement of the performance over the conventional BMA in terms of both subjective and objective quality of video sequences.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1067-1087
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• 2018

In a study for LiDAR data based building boundary extraction, usually dense point cloud was used to cluster building rooftop area and extract building outline. However, when we used DSM generated from stereo image matching to extract building boundary, it is not trivial to cluster building roof top area automatically due to outliers and large holes of point cloud. Thus, we propose a technique to extract building boundary semi-automatically from the DSM created from stereo images. The technique consists of watershed segmentation for using user input as markers and recursive MBR algorithm. Since the proposed method only inputs simple marker information that represents building areas within the DSM, it can create building boundary efficiently by minimizing user input.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.195-198
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• 2001

We proposes a new fingerprint minutia matching algorithm which matches the fingerprint minutiae by using local alignment. In general, fingerprint is deformed by Pressure and orientation when a user presses his fingerprint to the sensor. These nonlinear deformations change the position and the orientation of minutiae which decrease reliability of minutiae. Matching by using global alignment uses one alignment point. But, the problem with this method is that, due to the deformation, matching reliability of a minutia decreases as the distance from the alignment minutia increases. Matching by using local alignment overcomes this problem by considering minutiae which are located in a short distance boundary. Experimental results show that the performance of the proposed algorithm is superior to that of using global alignment.