• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1028-1040
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• 2000

Since image data has large data amount, proper image compression is necessary to transmit and store the data efficiently. Image compression brings about bit rate reduction but results in some artifacts. This artifacts are blocking artifacts, mosquito noise, which are observed in DCT based compression image, and ringing artifacts, which is perceived around the edges in wavelet based compression image. In this paper, we propose directional postprocessing technique which improved the decoded image quality using the fact that human vision is sensible to ringing artifacts around the edges of image. First we detect the edge direction in each block. Next we perform directional postprocessing according to detected edge direction. Proposed method is that the edge direction is block. Next performed directional postprocessing according to detected edge direction. If the correlation coefficients are equivalent to each directions, postprocessing is not performed. So, time of the postproces ing brings about shorten.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.9-15
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• 2016

Symmetry is everywhere in the world around us from galaxy to microbes. From ancient times symmetry is considered to be a reflection of the harmony of universe. Symmetry is not only a significant clue for human cognitive process, but also useful information for computer vision such as image understanding system. Application areas include face detection and recognition, indexing of image database, image segmentation and detection, analysis of medical images, and so on. The technique used in this paper extracts edges, and the perpendicular bisector of any two edge points is considered to be a candidate axis of symmetry. The coefficients of candidate axis are accumulated in the coefficient space. Then the axis of symmetry is determined to be the line for which the coefficient histogram has maximum value. In this paper, an improved method is proposed that utilizes the directional information of edges, which is a byproduct of the edge detection process. Experiment on 20 test images shows that the proposed method performs 22.7 times faster than the original method. In another test on 5 images with 4% salt-and-pepper noise, the proposed method detects the symmetry successfully, while the original method fails. This result reveals that the proposed method enhances the speed and accuracy of detection process at the same time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.87-88
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• 2012

Because intra prediction modes in H.264 are determined by the brightness continuity between neighboring blocks, they can be used as a method for extracting edge information in the compression domain. However, if we just consider 9 intra prediction modes in H.264 as 9 different edge directions, we have the following two problems. First, intra prediction modes tend to yield too many edge blocks, generating unnecessary edge information. Second, we may not need all 9 directional edges (including the DC type) in H.264 intra prediction modes. For example, the EHD (edge histogram descriptor) in MPEG-7 defines only 4 directional edge types, namely horizontal, vertical, diagonal (HVD) edges with $0^{\circ}$, $90^{\circ}$, $45^{\circ}$, and $135^{\circ}$. Here, semi-diagonal (SD) edge types with $112.5^{\circ}$, $157.5^{\circ}$, $22.5^{\circ}$, and $67.5^{\circ}$ in the intra prediction modes in H.264 are not used. In this paper. we prepose a method that removes unnecessary edges from the intra prediction modes by utilizing the total average coefficient of 4x4 blocks in each slice and assign SD edges to HVD (horizontal, vertical, diagonal, $0^{\circ}$, $90^{\circ}$, $45^{\circ}$, $135^{\circ}$) edges by the contextual information of the neighboring blocks. Experimental results show that the edges determined by the proposed method in the compression domain are comparable to those of the previous edge detection methods in the spatial domain.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.26-31
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• 2010

We proposed a new directional edge based interpolation, DEBI, by combining two weighted directional information to reduce blurred edges and annoying artifacts. Four isotropic gradient masks are employed in defining edge directions and they are proven to hold a first order derivative relation with respect to a rotating coordinate. Two minimum gradients among four absolute directional results are shown to be sufficient to describe slant edges efficiently. Compared with widely used bilinear and bicubic interpolation methods, the proposed algorithm results in a noticeable improvement along edge area.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.72-80
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• 1998

A method is proposed for directional vector quantization using the wavelet packets. After partitioning the wavelet packet coefficients into 9 edges according to the corresponding directions, it encodes and transmits locally dominant edges. The directions of the edges are encoded with a variable length coding and conditional switching of codebooks, while the contents of them with the vector quantization followed by the variable length index coding. The proposed algorithm is superior to various conventional image coding algorithms in the sense of PSNR, which is relatively more significant at very low bit rate such as 0.1~0.3 bpp. As the proposed algorithm preserves the edges which is the most important for the human visual system, it also provides the reconstructed images of good subjective quality even at very low bit rate.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.76-83
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• 1993

A morphological filtering algorithm using directional information is presented. Directional filtering technique is effective in reducing noises and preserving edges. The proposed directional filtering is composed of two stage filtering processes. The opening and closing operations in the lst stage are performed for the pixels is aligned to the vertical, horizontal, and two diagonal directions, respectively. The opening operation supresses the positive impulse noises, while the closing operation the negative ones. Then, each directional result and their average value are filtered by the opening or closing operations in the 2nd stage. The averaging operation diminishes the effects of Gaussian noises in the homogeneous regions. Thus, the morphological operation in the 1 st stageremoves the impulse noises and in 2nd stage reduces. Gaussian ones. The experimental results show that the proposed filtering is superior to the existing nonlinear filtering in the aspects of the subjective quality. Also, the morphological filtering method reduces the computational loads.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.483-488
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• 2008

An active omni-directional raging system using an omni-directional vision with structured light has many advantages compared to the conventional ranging systems: robustness against external illumination noise because of the laser structured light and computational efficiency because of one shot image containing $360^{\circ}$ environment information from the omni-directional vision. The omni-directional range data represents a local distance map at a certain position in the workspace. In this paper, we propose a matching algorithm for the local distance map with the given global map database, thereby to localize a mobile robot in the global workspace. Since the global map database consists of line segments representing edges of environment object in general, the matching algorithm is based on relative position and orientation of line segments in the local map and the global map. The effectiveness of the proposed omni-directional ranging system and the matching are verified through experiments.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.631-634
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• 1999

In this work, a new algorithm for canceling MRI artifact in the image plane is presented. In the conventional approach, the motions in the X(readout) direction and Y(the phase encoding) direction are estimated simultaneously. However, the feature of each X and Y directional motion is different. First, we notice that the X directional motion corresponds to a shift of the X directional spectrum of the MRI signal, and the non zero area of the spectrum just corresponds to X axis projected area of the density function. So the motion is estimated by tracing the edges of the spectrum, and the X directional motion is canceled by shifting the spectrum in inverse direction. Next, the Y directional motion is canceled using a new constraint, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by simulations.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1075-1078
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• 1999

In this study, a new algorithm for canceling MRI artifacts through the translational motion of image plane is presented. Bloating is often makes problems in a clinical diagnosis. Assuming that the head moves up and down due to breathing, rigid translational motions in only y(phase encoding axis) direction is treated. First, we notice that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal, and the non zero area of the spectrum just corresponds to x axis projected area of the density function. So the motion is estimated by tracing the edges of the spectrum, and the x directional motion is canceled by shifting the spectrum in inverse direction. Next, the y directional motion is canceled using a new constraint, with which the motion component and the true image component can be separated. Finally, the effectiveness of this algorithm is shown by using a phantom with simulated motions.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.49-57
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• 2000

In this study, a new algorithm for canceling a MRI artifact due to the translational motion In the image plane is described. Unlike the conventional iterative phase retrieval algorithm, in which there is no guarantee for the convergence, a direct method for estimating the motion is presented. In previous approaches, the motions in the x(read out) direction and the y(phase encoding) direction were estimated simultaneously. However, the feature of x and y directional motions are different from each other. By analyzing their features, each x and y directional motion is canceled by the different algorithms in two steps. First, it is noticed that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal, and the non-zero area of the spectrum just corresponds to the projected area of the density function on the x axis. So the motion is estimated by tracing the edges between non-zero area and zero area of the spectrum, and the x directional motion is canceled by shifting the spectrum in an reverse direction. Next, the y directional motion is canceled by using a new constraint condition, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by using a phantom image with simulated motion.