• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1635-1644
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• 1993

In this paper, we examine the statistical characteristics of edge enhancing filters and their efficacy as preprocessing operator before edge detection. In particular, edge enhancing filters called the Comparison and Selection(CS), Hachimura-kuwahara(HK), and Selective Average(SA) filters are considered. These filters can reduce noise while producing step-type edges, thus seem to be effective for preprocessing noisy images prior to applying edge detecors. The ability of edge enhancing filters to suppress white Gaussian noise and the error probabilities occured during the edge detection following SA prefiltering are evaluated statistically through numerical analysis. The effect of prefiltering on edge detection is assessed by applying the edge enhancing fitters to a noise image degraded by additive white noise prior to applying the Sobel operator and the Laplacian of Gaussian( LoG ) operator, respectively. It is shown that the edge enhancing filters tend to produce ideal step-type edges while reducing the noise reasonably well, and the use of edge enhancing filters prior to edge detection can improve the performance of subsequent edge detector.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.600-602
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• 2001

본 논문은 웨이블릿 필터를 이용하여 홍채영상의 에지를 검출하고 패턴매칭 기법을 적용하여 홍채의 결함조직에 대한 위치를 추정하는 연구이다. 필터는 웨이블릿 변환을 이용한 2차원 주파수 영역의 고역통과 필터를 사용하여 홍채영상의 에지를 검출하고, 이를 표준진단패턴과 오버랩 매칭으로 결함조직을 검출한다. 실험결과 처리속도가 기존의 에지검출기법에 비해 처리속도향상과 에지검출영상의 PSNR 증가에 따라 오버랩 패턴매칭기법에 의한 인식률에서 92%로 홍채결함조직을 자동 진단시스템에 응용 가능하다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.751-754
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• 2002

장면 전환 검출(Scene Change Detction)수행 방법으로 객체 인식에 의한 검출이 아닌 전체 영상의 전역적인 형태 흐름을 기반으로 한 검출 시스템을 제안한다. 형태흐름의 변하는 영상의 전체적 모양에 관한 전역적 특징을 이용하여 영상내에 존재하는 에지, 에지의 중심, 표준 편차 및 에너지의 분포 변환에서 추출할 수 있다. 본 논문에서는 효율적인 에지 검출을 위하여 미디언 필터와 개량형 라플라시안 필터를 사용한다. 일반적으로 이용되는 라플라시안 필터를 사용하였을 때 획득할 수 있는 에지 정보보다 우수한 정보를 얻을 수 있었고 보다. 정착한 장면 전환을 검출하기 위해 이 에지 정보를 수평$(0^{\circ})$, 수직$(90^{\circ})$, 대각선$(45^{\circ},\;135^{\circ})$ 방향으로 세분화한 뒤에 프레임간에 각도 방향별 에지 정보를 파악하여 방향별 에지 에너지(Energy of edge)의 상대적인 성분 분포의 비교를 수행함으로써 정확성을 높였다.

• 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 Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2447-2456
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• 1998

Edge detection in the presence of noise is a well-known problem. this pper atempts to implement edge detection algorithms using fuzzy reasoning of fuzzy membership models. It examines an application-motived approach for solving the problem. Our approach is divided into three stages; fitering, segmentation and tracing. Filtering removes the noise from the original image and segmentation determines the edges and deects them. Finally, tracing assembles the edges into the related structure. Proposed method can be used effectively on these procedures by using fuzzy reasoning based on fuzzy models. In is compared with the previous edge detectio algorithms with fvorable results. Simulation results of the research are presented and discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.437-440
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• 2022

In modern society, the use of the image processing field is increasing rapidly due to the 4th industrial revolution and the development of IoT technology. In particular, edge detection is widely used in various fields as an essential preprocessing process in image processing applications such as image classification and object detection. Conventional methods for detecting an edge include a Sobel edge detection filter, a Roberts edge detection filter, a Prewitt edge detection filter, Laplacian of Gaussian (LoG), and the like. However, existing methods have the disadvantage of showing somewhat insufficient performance of edge detection characteristics in a low-light level environment with low contrast. Therefore, this paper proposes an edge detection algorithm based on contrast analysis to increase edge detection characteristics even in low-light level environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.202-207
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• 2021

One of the most important tasks in image processing is noise filtering. Noise removal in image is a difficult task due to many reasons such as nonstationary sequences and corrupted by various types of noise. Human's visual perception is heavily based on the edge information. Thus, noise filtering must preserve edges. To remove the noise, we usually use the square-shaped median filter. They possess mathematical simplicity but have the disadvantages that blur the edges. In this paper we consider a new technique for image restoration using a weighted octagonal median filter. The technique consists of simple hypothesis test for edge detection, and we use the weighted octagonal-shaped moving window. The new technique is applied to noise corrupted image and experimental results are compared to the results of the square-shaped median filter and the cross-shaped median filter.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.04b
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• pp.871-874
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• 2001

장면 변환 검출(Scene Change Detection)수행 방법으로 객체 인식에 의한 검출이 아닌 전체영상의 형태 흐름을 기반으로한 검출시스템을 제안한다. 형태흐름의 변화는 영상내에 존재하는 에지(edge), 에지의 중심(Center of edge), 분산(Varience of edge) 및 표준 편차(Standard deviation of edge)의 분포 변화에서 추출할 수 있다. 본 논문에서는 효율적인 정보의 추출을 위해서 보다 정확한 에지의 정보 추출이 중요하다. 영상의 히스토그램을 8단계로 분류한 후, 각 단계에 맞는 임계치를 에지검출 수행에 사용하였으며, 효율적인 에지검출을 위하여 개량형 라플라시안 필터를 제안한다. 일반적으로 이용되는 필터를 이용하였을 때 획득할 수 있는 에지 정보보다 우수한 정보를 얻을 수 있었다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.281-286
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• 2013

In this paper, we propose a noise estimation method using edge detection. It is a filter-based noise estimation method. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use a modified rational filter which is robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of images and has better results than those of conventional filter-based noise estimation methods.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.180-186
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• 2012

In this paper, a method of edge detection from low contrast and noisy images which contain hexagonal shape is proposed. This method is based on the combination of laplacian gaussian filter and an idea of filters which are dependent on the shape. First, an algorithm which has six masks as its extractors to detect the hexagonal edges especially in the comers is used. Here, two tricom filters are used to detect the tricom joints of hexagons and other four masks are used to enhance the line segments of hexagonal edges. As a natural image, a corneal endothelial cell image which usually has a regular hexagonal shape is selected. The edge detection of hexagonal shapes in this corneal endothelial cell is important for clinical diagnosis. Next, The proposal algorithm and other conventional methods are applied to noisy hexagonal images to evaluate each efficiency. As a result, this proposal algorithm shows a robustness against noises and better detection ability in the aspects of the signal to noise ratio, the edge coineidence ratio and the detection accuracy factor as compared with other conventional methods.