• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.2
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• pp.162-171
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• 1991

This paper presents an algorithm for compressing image data by separating the image into two parts. I.e. edge image containing high-frequency components and non-edge image containing low-frequency components of image. The edge image is extracted by using 8 level compass gradient masks and the non-edge image is obtained by removing the edge image from the original image. The edge image is coded by Huffman run-length code and the non edge image is transformed first by DCT and the transformed images is coded next by a quantized bit allocation table. For an example image. GIRL. the proposed algorithm shows bit rate of 0.52 bpp with PSNR of 36dB.

• Journal of the Korean Society of Combustion
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• v.14 no.1
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• pp.25-30
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• 2009

Propagation rates ($U_{edge}$) of various premixed, twin edge-flames were measured as a function of global strain rate ($\sigma$), mixture strength, and Lewis number (Le). Using a counterflow slot-jet burner with electrical heaters at each end, both advancing (positive $U_{edge}$) and retreating (negative $U_{edge}$) edge-flames can be studied as they propagate along the long dimension of the burner. Experimental results are presented for premixed methane/air twin flames in terms of the effects of $\sigma$ on $U_{edge}$. Both low-$\sigma$ and high-$\sigma$ extinction limits were discovered for all mixtures tested. As a result, the domain of edge-flame stability was obtained in terms of heat loss factor and normalized flame thickness, and comparison with the numerical result of other researchers was also made. For low ($CH_4/O_2/CO_2$) and high ($C_{3}H_{8}$/air) Lewis number cases, propagation rates clearly show a strong dependence on Le.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.197-200
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• 2007

Edge representing the boundary between two regions with the large brightness difference in image includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge in according to duration time and the amplitude of brightness variation, and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.05a
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• pp.49-52
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• 2008

The numerical analysis for gas temperature of turbine blade surface has been performed to investigate development of temperature with various blade edge shape. Two different types of the turbine which one is "Sharp" edge and the other is "Round" edge was modeled. Computations have been carried out several turbine rotational speeds in the range from 0 to 10,000 rpm for the each types of turbine edge shape. As a result, the more rotational speed of turbine increased, the more turbine blade's temperature decreased. It is also found that the surface temperature of turbine blades for sharp type edge were lower than the round type edge.

• Journal of Korea Multimedia Society
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• v.8 no.2
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• pp.174-180
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• 2005

Points of sharp variations in image are the most important components when we analyze the features of image. And they include a variety of information about image's shape and location etc. So a lot of researches for detecting edges have been continued. Edge detection operators which were used at the early stage of the research were to utilize relations among neighboring pixels. These methods detect edge at all boundaries, therefore they perform edge detection twice about curves below some width such as line-edge. In the meantime, wavelet transform which is presented as a new technique of signal processing field provides multiscale edge detection and is being applied widely in many fields that analyze edge-like characteristic. Therefore, in this paper we detected line-edge with new 2-D wavelet function which is independent of line's width.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.423-428
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• 2005

This paper proposes a new edge detection method using a $3{\times}3$ ideal binary pattern and lookup table (LUT) for the mobile robot localization without any parameter adjustments. We take the mean of the pixels within the $3{\times}3$ block as a threshold by which the pixels are divided into two groups. The edge magnitude and orientation are calculated by taking the difference of average intensities of the two groups and by searching directional code in the LUT, respectively. And also the input image is not only partitioned into multiple groups according to their intensity similarities by the histogram, but also the threshold of each group is determined by fuzzy reasoning automatically. Finally, the edges are determined through non-maximum suppression using edge confidence measure and edge linking. Applying this edge detection method to the mobile robot localization using projective invariance of the cross ratio. we demonstrate the robustness of the proposed method to the illumination changes in a corridor environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.89-96
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• 2009

In this paper, we propose an efficient deinterlacing algorithm which is an edge dependent interpolation based on edge direction refinement. The conventional edge dependent interpolation algorithms have a visually better performance than any other Intra-field deinterlacing algorithms. However they are very sensitive to noise due to the failure of estimating edge direction. In order to exactly detect edge direction, our method detects edge direction of around interpolated pixel and refines the edge direction using weighted median filter. Simulation results have shown the efficacy of the proposed method with significant improvement over the previous methods in terms of the objective PSNR quality as well as the subjective image quality.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.328-330
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• 2015

Edge is a characteristic information that can easily obtain the size, direction and location of objects included in the image, and the edge detection is utilized as a preprocess processing in various image processing application sectors such as object detection and object recognition, etc. For the conventional edge detection methods, there are Sobel, Prewitt and Roberts. These existing edge detection methods are easy to implement but the edge detection characteristics are somewhat insufficient as fixed weighted mask is applied. Therefore, in order to compensate the problems of existing edge detection methods, in this paper, an edge detection algorithm was proposed after applying the weighted value according to the standard deviation and means within the local mask.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.133-141
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• 2005

An edge is where the intensity of an image moves from a low value to high value or vice versa. The edges tell where objects are. their shape and size. and something about their texture. Many traditional edge operators are derivative based and perform reasonably well for simple noise-free images. In recent, statistical edge detectors for complex images with noises have been described. This paper compares and analysis the performance of statistical edge detectors based on the T test and Wilcoxon test, and mathematical edge detectors based on Sobel operator, and the well-known Canny detector and Wavelet transformation detector, and provides the implementation of these edge detectors using Java on the web.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1156-1161
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• 2007

Edge representing the boundary between two regions with the large briskness difference in mage includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge according to duration time and the amplitude of brightness variation and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.