• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.355-362
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• 2009

A new intra field deinterlacing algorithm with edge map in the image block is introduced. Conventional deinterlacing methods usually employ edge-based line average algorithm within pixel-by-pixel approach. However, it is sensitive to variation of intensity. To reduce this shortcoming, we proposed edge direction vector computed by edge map, and also its interpolation technique. We first introduce an edge direction vector, which is computed by Sobel mask, so that finer resolution of the edge direction can be acquired. The proposed edge direction vector oriented deinterlacer operates by identifying small pixel variations in five orientations, while weighted averaging to estimate missing pixel. According to the edge direction of the direction vector, we calculate weights on each edge direction. These weight values multiplied by the candidate deinterlaced pixels in order to successively build approximations of the deinterlaced sequence.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06a
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• pp.185-188
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• 1998

본 논문에서는 새로운 예측 방법을 사용한 웨이브릿 영상 압축 방식을 제안한다. 에지는 시각적으로 매우 중요한 성분이며 밴드간에도 높은 상관도를 가지고 있다. 또한 에지는 각 밴드의 성질에 맞는 일정한 방향을 가지고 있다. 본 논문에서는 자식 계수들의 배열이 밴드 방향에 따라 방향성을 가진다는 것을 예측에 이용하여 새로운 트리를 통해 영상을 압축하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1221-1227
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• 2015

Edge detection is one of the important technologies to simplify images in the text, lane and object recognition implementation process, and various studies are actively carried out at home and abroad. Existing edge detection methods include a method to detect edge by applying directional gradient masks in spatial space, and a mathematical morphology-based edge detection method. These existing detection methods show insufficient edge detection results in excessively dark or bright images. In this regard, to complement these drawbacks, we proposed an algorithm using the Sobel and histogram equalization among the existing methods.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.91-97
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• 2007

Points of sharp variations in signals are the most important factors when analyzing the features of signals. And in the image, edges include diverse information such as the locations, shape and material. There have been a variety of researches on edge detections, among them, methods based on convolution in the spatial domain have been most popular. However at the early stage of the method, if the noise and many kinds of edges exist in the image, it is not easy to separate edges selectively from corrupted images by noise. In meantime, the wavelet transform for multiscale edge detection is being applied widely to analyze the properties of images in various fields. In this paper, we suggest a robust wavelet-based method, which selectively detects line-edge elements from images in the presence of noise.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.1-12
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• 2008

This paper presents automatic moving object detection method using the rotating camera covering larger area with a single camera. The proposed method is based on the edge segment matching which robust to the dynamic environment with illumination change and background movement. The proposed algorithm presents an edge segment based background panorama image generation method minimizing the distortion due to image stitching, the background image generation method using Generalized Hough Transformation which can reliably register the current image to the panorama image overcoming the stitching distortions, the moving edge segment extraction method that overcome viewpoint difference and distortion. The experimental results show that the proposed method can detect correctly moving object under illumination change and camera vibration.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1066-1072
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• 2009

This paper proposes a method to reduce the complexity and improve the performance for gentle-slope edges which is the disadvantage of deinterlacing algorithm using the new edge-directed interpolation. To improve the performance for gentle-slope edges, the proposed algorithm increases the number of neighboring reference pixels. To reduce the artifacts and the computational complexity, the proposed algorithm adaptively determines the number of neighboring reference pixels. With computer simulations for a variety of images, it shows that the proposed algorithm provides improved performance in PSNR and subjective evaluation compared with the existing algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.136-138
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• 2022

Edge detection includes information such as the shape, position, size, and material of an object with respect to an image, and is a very important factor in analyzing the characteristics of the image. Existing edge detection methods include Sobel edge detection filter, Roberts edge detection filter, Prewitt edge detection filter, and LoG (Lapacian of Gaussian) using secondary differentials. However, these methods have a disadvantage in that the edge detection results are somewhat insufficient because a fixed weight mask is applied to the entire image area. Therefore, in this paper, we propose an edge detection algorithm that increases edge detection characteristics by considering the center pixel in the mask. In addition, in order to confirm the proposed edge detection performance, it was compared through simulation result images.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.225-230
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• 2011

In this paper, we propose the segmentation method for detecting the facial region by using watershed based on depth information and merge algorithm. The method consists of three steps: watershed segmentation, seed region detection, and merge. The input color image is segmented into the small uniform regions by watershed. The facial region can be detected by merging the uniform regions with chromaticity and edge constraints. The problem in the existing method using only chromaticity or edge can solved by the proposed method. The computer simulation is performed to evaluate the performance of the proposed method. The simulation results shows that the proposed method is superior to segmentation facial region.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.237-240
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• 1996

본 논문에서는 방향성을 갖는 새로운 공간적응 조절연산자와 비선형필터를 이용한 제한 반복적 영상복원 알고리듬을 제안하고 제안한 알고리듬의 수렴성에 대하여 분석을 하고 있다. 일반적인 제한반복적 영상복원 기법에서는 열화된 영상을 복원하는 과정에서 에지 및 경계부분의 재번짐이 지나친 잡음성분의 증폭에 의한 고리현상 등이 발생한다. 이러한 문제들을 해결하기 위하여 본 논문에서는 다음과 같은 기법을 도입하고 있다. 첫째는, 방향성을 갖는 새로운 공간적응 조절연산자를 적용하여 에지 등의 재번짐을 막고 고주파수 영역의 복원성능을 개선하고 있다. 둘째로, 적응적인 비선형필터를 사용하여 잡음성분과 같은 고주파수 영역의 지나친 증폭에 따른 문제를 해결하고 있다. 그리고, 제안한 논문의 안정성과 수렴성을 보장하기 위한 조건을 분석하고 있다. 열화된 영상에 대하여 실험한 결과, 기존의 다른 결과보다 우수한 성능이 있었고, 특히, 에지의 복원성능 및 고리현상의 제거에 두드러진 특징을 나타내었다.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.110-113
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• 2002

통신과 멀티미디어 기술의 발전으로 대용량의 멀티미디어 자료에 대한 효율적인 검색 방법이 대두되고 있다. 본 논문에서 다루고자 하는 동영상 장면전환 검출 연구는 멀티미디어 데이터베이스의 내용기반 비디오 정보검색 및 비디오 데이터 인덱싱 구현의 기반이 되는 첫번째 단계의 핵심적인 분야에 속한다. 비디오 데이터를 내용기반으로 처리 하기 위해서는 우선 비디오데이터를 연속성에 의한 유사 영역으로 분할하여야 한다. 동영상을 분할하기 위한 방법으로 비디오의 불연속점을 찾아내는 장면전환 검출이 널리 사용되어 이에 관한 연구가 활발하게 진행되고 있다. 본 논문에서는 기존의 방법인 히스토그램 방식과 에지검출 방식의 장단점을 비교하고 두 알고리즘의 장점을 혼합한 방식을 제안하였다. 영상을 1차로 히스토그램의 피크값과 계곡특징값을 이용하고 2차로 에지검출 방식으로 두 단계로 나누어 처리하여 속도향상과 정확도를 높이고자 하는 방법을 제안하였다. 그리고 실험을 통하여 기존의 방법들과의 비교 분석을 통하여 성능평가를 하고자 한다.