• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.100-103
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• 2014

Currently, edge detection is utilized in various areas. Edge detection is the preprocessing process for image processing in general, and this is a technology that is considered essential for image processing. According, research on this subject is carried out incessantly. Edge has important image related elements such as size, direction and location of the object of an image. Numerous methods were proposed for the detection. Among them, the representative methods are Sobel, Prewitt, Roberts, Laplacian. However, these existing methods are rather lacking when it comes to the edge detection characteristics in case of the image with mixed noise. Therefore, this study presented edge detection method that utilizes median and average values for the elements depending on the size and location of local mask.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.4
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• pp.280-286
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• 1986

A newmethod of fast mask operators for edge detection is proposed, which is based on the matrix factorization. The output of each component in the multi-directional mask operator is obtained adding every image pixels in the mask area weighting by corresponding mask element. Therefore, it is same as the result of matrix-vector multiplication like one dimensional transform, i, e, , trasnform of an image vector surrounded by mask with a transform matrix consisted of all the elements of eack mask row by row. In this paper, for the Sobel and Prewitt operators, we find the transform matrices, add up the number of operations factoring these matrices and compare the performances of the proposed method and the standard method. As a result, the number of operations with the proposed method, for Sobel and prewitt operators, without any extra storage element, are reduced by 42.85% and 50% of the standard operations, respectively and in case of an image having 100x100 pixels, the proposed Sobel operator with 301 extra storage locations can be computed by 35.93% of the standard method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.252-257
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• 2007

우리나라의 항만은 수 출입화물의 99.5%를 처리하며, 육로 및 철도 수송 물동량의 기종점 역할을 수행하는 중요한 곳으로서 항만 물동량의 신속한 처리와 자동화 시스템에 의한 비용절감은 엄청난 효과를 가져온다. 따라서 본 논문에서는 항만에서 취급하는 컨테이너를 자동으로 식별할 수 있는 자동화 방법을 제안한다. 실제 컨테이너 영상을 그레이 영상으로 변환한 후, 프리윗 마스크(Prewitt-Mask)를 적용하여 윤곽선을 추출하고 컨테이너를 식별할 수 있는 개별 식별자의 형태학적 특징 정보를 이용하여 식별자 후보영역을 검출한다. 검출된 식별자 후보영역은 개별 식별자 영역외에 잡음 영역이 포함되어 있으므로 4방향 윤곽선 추적 알고리즘과 Grassfire 알고리즘을 적용하여 잡음을 제거하고 개별 식별자들을 각각 객체화한다. 잡음이 제거된 식별자 후보 영역에서 객체화 한 개별 식별자는 컨테이너 식별을 위해 FCM 기반 퍼지 RBF 네트워크를 적용하여 인식한다. 본 논문에서 제안한 컨테이너 식별자 인식 방법의 성능을 평가하기 위해 실제 컨테이너 영상 300장을 대상으로 실험한 결과, 기존의 방법보다 인식 성능이 개선되었음을 확인할 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.313-319
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• 2007

In this paper, we propose a novel method to extract an area of car licence plate and codes of vehicle number from a photographed car image using features on vertical edges and a new Fuzzy neural network algorithm to recognize extracted codes. Prewitt mask is used in searching for vertical edges for detection of an area of vehicle number plate and feature information of vehicle number palate is used to eliminate image noises and extract the plate area and individual codes of vehicle number. Finally, for recognition of extracted codes, we use the proposed Fuzzy neural network algorithm, in which FCM is used as the learning structure between input and middle layers and Max_Min neural network is used as the learning structure within inhibition and output layers. Through a variety of experiments using real 150 images of vehicle, we showed that the proposed method is more efficient than others.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.901-908
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• 2016

Edge is the basic characteristic of image, edge detection is very important in image processing applications and computer vision area. Many studies are being performed to detect these edges by domestic and foreign researchers. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask are widely used and morphological gradient which uses dilation and erosion among morphology process techniques is also widely used. But these methods does not detect edges well in the diagonal direction or gradually changing image parts. Accordingly, in this paper, the modified top-hat and bottom-hat transform algorithms which are detecting edges well in the parts of diagonal direction or gradually changing image are proposed. The proposed algorithms present the detected edge images compared with the conventional methods and are evaluated performance by using cosine similarity.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1051-1058
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• 2018

This paper propose image processing algorithm to prevent safety accidents near by subway platform screen door(PSD). First, edges of the subway PSD images are detected and the boundary line between PSD and subway platform is detected to decide people's approach to the PSD using Hough transform. To do this, we draw the boundary line between the PSD and platform, to detect the boundary line and to decide the people's approach to the detected line is completely connected or not. Generally, edge is the basic characteristic of image; thus, edge detection is very important in image processing applications and computer vision area. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask, and morphological gradient from the structuring element of view and Canny edge detector are widely used. In this paper, we propose the detection algorithm about the people's approach to the subway PSD to prevent the safety accidents by using Canny edge detector and Hough transform and the computer simulation shows the results.

• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.5 s.57
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• pp.169-179
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• 2009

The purpose of this paper is to find an efficient heat source to amplify the surface temperature of damaged concrete structures for infrared thermography. we compare two different heat sources of far-infrared lamp and halogen lamp each other for their efficiency. The two heat sources were applied to the concrete specimens. Two different concrete specimens were used: one was the concrete containing internal void and the other was wrapped with partially unbonded fiber reinforced polymer sheet. it was found that the far-infrared lamp was more efficient than the halogen lamp. In addition, we propose a new algorithm to make the damage zone displayed clear in the image obtained from the thermographic operation. The algorithm is a combination of Gauss filtering process and the Prewitt mask operation.