• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.135-140
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• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.256-259
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• 2010

본 논문에서는 적응적 평활화 필터를 이용한 스캔된 하프톤 문서의 하프톤 잡음 제거 방법을 제안한다. 하프톤 잡음은 잡음의 편차가 커서 에지 영역과 유사한 특성을 나타내므로 일반적인 에지 보존 평활화 필터를 적용할 경우에는 잡음 제거 효과가 떨어진다. 또한 인쇄물에 주로 사용되는 집중형 도트 방식의 하프톤은 컬러 영상에서 채널간의 간섭 현상으로 인해 모아레 패턴을 생성한다. 따라서 본 논문에서는 스캔된 하프톤 문서의 하프톤 잡음과 모아레 패턴을 효과적으로 제거하기 위해 하프톤 잡음의 방향성에 기반한 적응적 평활화 필터 방법을 제안한다. 하프톤 잡음의 경우 영상의 에지와 달리 등방성을 가지므로 영상을 블록 단위로 나누어 지배적인 에지의 크기와 방향성을 살핌으로써 적응적 평활화 필터를 구성할 수 있다. 실험 결과, 제안하는 방법은 다양한 인쇄 매체를 통해 생성된 하프톤 문서에 대하여 효과적으로 하프톤 잡음을 제거하면서도 영상의 에지를 보존하는 것을 확인할 수 있었다.

• Journal of the Korea Computer Industry Society
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• v.3 no.12
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• pp.1725-1736
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• 2002

We describe a characteristic behavior of edge signal intensity, the strictly monotonic variation of intensity across edges and propose a new algorithm for edge detection based on it. We define an extended directional derivatives, which is nonlocal and beyond scaling in the pixel space, to describe that the algorithm is adaptive to the various widths of edges and relevant as an optimal edge detection algorithm. As an industrial application of the algorithm, we discuss a simple computer vision procedure for an example of visual inspection.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.330-333
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• 2003

영상 분류는 내용기반 영상검색에서 부적절한 이미지를 효과적으로 걸러 낼 수 있게 하여 영상 검색의 성능을 향상 시키는데 큰 역할을 하게 된다. 따라서 최근 의미 있는 영상의 분류가 내용기반검색분야에서 중요한 과제로 대두되고 있다. 본 논문에서는 에지 정보를 이용해서 객체 영상을 인공객체영상과 자연객체영상으로 분류하는 방법을 제안한다. 직선형태의 에지를 많이 가지는 인공객체의 경우 에지 방향 히스토그램의 에너지가 자연객체에 비해 높은 값을 가지기 때문에 객체 분류에 유용한 정보로서 에지 정보를 활용하였다. 또한 에너지 값을 낮추는 원형의 에지가 인공객체영상에서 주로 발견되는 점을 이용하여, 제거에 의해 분류의 성능을 높이고자 하였다. 한편 가버 필터를 이용한 분류 결과에 비해 에지 정보를 이용한 분류가 성능 면에서 보다 나은 결과를 얻을 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.151-156
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• 2006

This paper presents an background edge generation based automatic algorithm for detection of moving objects under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally, aligning and reorganizing this images. We develop an efficient approach for robust panoramic background edge generation as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The proposed method can be successfully realized in various monitoring systems like intrusion detection as well as video surveillance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.506-512
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• 2003

The edge detection has been so far under a lot of studies on its methods, as a very important part of image recognition. Never the less the correct detection of the edge has been yet a difficult problem because of the various scopes of detection according to the applied field. One of those problems to be solved is the edge detection in images with noise. This paper presents an efficient method which removes noise and detect edge in the same framework based on fuzzy logic. The method consists of two steps. First, an efficient filtering is applied to eliminate the noise from original image. The filtering is performed by utilizing fuzzy MIN-MAX operator in three directions such as vertical, horizontal and diagonal angle of 3${\times}$3 mask. Second, edges are detected by using extended fuzzy Shanon Function.

• 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.

• The Journal of Korean Association of Computer Education
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• v.13 no.4
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• pp.77-86
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• 2010

In this paper, we propose a real time post-processing visual enhancement technique to reduce the blocking artifacts in block based DCT decoded image for mobile devices that have allocation of the restricted resource. In order to reduce the blocking artifacts effectively even while preserving the image edge to the utmost, the proposed algorithm uses the deblocking filtering or the directional filtering according to the edge detection of the each pixel. After it is discriminated that the pixel to apply the deblocking filtering belongs again to the monotonous area, the weighted average filter with the adaptive mask is applied for the pixel to remove the blocking artifacts. On the other hand, a new directional filter is utilized to get rid of staircase noise and preserve the original edge component. Experimental results show that the proposed algorithm produces better results than those of the conventional algorithms in both subjective and objective qualities.

• Journal of Korea Multimedia Society
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• v.8 no.2
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• pp.164-173
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• 2005

Painterly rendering may bring various results through the parameters that determine the characteristics of brush strokes such as, color, orientation, size, and shape. In this paper, we propose the most adaptive brush stroke generation for source images, using reference data. Our algorithm used Colors formed by actual palette colors from artists. To create the palette, we have referred mostly to colors used in Van Gogh's works and determined the color of brush strokes by transferring it to the most similar one, through comparing colors used in source images and the palette colors. Also, In order to emulate a brush stroke with dynamic properties like Van Gogh styles we have applied a brush stroke orientation that surrounds the edges by referring to the edge orientation of source images. The sizes were determined depending on the different sizes of the objects from wide to narrow brushes. Finally, we applied spline curve shapes to simulate curves and swirls like Van Gogh styles. The brush strokes created in such method, were applied separately according to its segmented images, and composed after rendering.