• Title/Summary/Keyword: Image edge

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EDGE-DETECT INTERPOLATION FOR DIRECT DIGITAL PERIAPICAL IMAGES (경계강조 보간법을 이용한 디지털방사선사진상의 개선에 관한 연구)

  • Song Nam-Kyu;Koh Kwang-Joon
    • Journal of Korean Academy of Oral and Maxillofacial Radiology
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    • v.28 no.1
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    • pp.73-85
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    • 1998
  • The purpose of this study was to aid in the use of the digital images by edge-detect interpolation for direct digital periapical images using edge-detect interpolation. This study was performed by image processing of 20 digital periapical images; pixel replication, linear non-interpolation, linear interpolation. and edge-sensitive interpolation. The obtained results were as follows : 1. Pixel replication showed blocking artifact and serious image distortion. 2. Linear interpolation showed smoothing effect on the edge. 3. Edge-sensitive interpolation overcame the smoothing effect on the edge and showed better image.

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A Study on Edge Detection using Local Mask in AWGN Environments (AWGN 환경에서 국부 마스크를 이용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Hwang, Yeong-Yeun;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.801-803
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    • 2014
  • In the modern society, image processing is utilized in various fields. Edge detection used for image processing as such is essential for most of the applications. Accordingly, there are studies conducted both in and out of Korea in order to detect edge. Representative edge detection methods include Sobel, Prewitt and Roberts. However, these methods are rather limited when it comes to the edge detection characteristics when used for the image with damaged AWGN(additive white Gaussian noise). Thus, this paper presented edge detection method utilizing local mask in order to overcome the shortcomings of the existing methods.

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Adaptive morphological Wavelet-CNN Algorithm for the Color Image Edge detection (컬러 영상 에지 검출을 위한 적응 형태학적 WCNN 알고리즘)

  • Beak, Young-Hyun;Moon, Sung-Rung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.4
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    • pp.473-480
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    • 2004
  • This paper presents a new edge detection algorithm in color image. The proposed Adaptive morphological Wavelet-CNN algorithm is divided into two parts : The Adaptive morpholog and WCNN(Wavelet Cellular Neural Networks). It detects the optimal edge with applying this color image to WCNN algorithm, after it does level up a boundary side of a color image by using the adaptive morphology as the threshold of an input color image. Also, it is used not a conventional fixed mask edge detection method but variable mask method which is called a variable BBM. Finally, to show the feasibility of the proposed algorithm, this paper provides by simulation that the color image consists of 30.

Edge Enhancement of Halftone Image using Adaptive Error Diffusion Method (적응적 오차 확산법을 이용한 하프톤 영상의 경계선 개선)

  • Kim, Sang-Chul;Chien, Sung-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.6
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    • pp.96-104
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    • 2011
  • A halftoning method is used to obtain a binary image visually similar to a continuous gray-level image through the image output devices employing the limited number of gray-levels. As a halftoning method, the error diffusion method is widely used in various applications because of its low computational complexity and good image quality. However, this method weakens the edge in the process of error diffusion to the neighboring pixels. In this case, degradation of the edge quality and damage of the vivid image is expected. To solve these problems, the proposed method determines the adaptive error filter considering the error information of the present pixel and edge distribution of the neighbor pixels. Compared with the conventional methods for enhancing edges, the proposed method involves relatively a few process resources because of its simple procedure, still considerably improving the edges in the halftone image. To evaluate the objective image quality, the performance of the proposed method is compared with that of the conventional method in terms of the edge correlation and the local average accordance.

Color Image Segmentation for Region-Based Image Retrieval (영역기반 이미지 검색을 위한 칼라 이미지 세그멘테이션)

  • Whang, Whan-Kyu
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.1
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    • pp.11-24
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    • 2008
  • Region-based image retrieval techniques, which divide image into similar regions having similar characteristics and examine similarities among divided regions, were proposed to support an efficient low-dimensional color indexing scheme. However, color image segmentation techniques are required additionally. The problem of segmentation is difficult because of a large variety of color and texture. It is known to be difficult to identify image regions containing the same color-texture pattern in natural scenes. In this paper we propose an automatic color image segmentation algorithm. The colors in each image are first quantized to reduce the number of colors. The gray level of image representing the outline edge of image is constructed in terms of Fisher's multi-class linear discriminant on quantized images. The gray level of image is transformed into a binary edge image. The edge showing the outline of the binary edge image links to the nearest edge if disconnected. Finally, the final segmentation image is obtained by merging similar regions. In this paper we design and implement a region-based image retrieval system using the proposed segmentation. A variety of experiments show that the proposed segmentation scheme provides good segmentation results on a variety of images.

Wear Mwarsurement of Single Crystal Diamond Tool Using Image Processing (영상처리를 이용한 초정밀가공용 다이아몬드 공구의 마멸 측정)

  • 양민양
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.04a
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    • pp.135-139
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    • 1996
  • In this a paper, a new method to measure the wear of the single crystal diamond(SCD) tool using image processing is presented. To increase resoultion, high magnifying lens is used and to enlarge the measurement field of view, a image region matching method is applied. The shape of SCD tool is modeled by mathematical analysis. Cutting edge chipping and wear are calculated by the model. This method is proved to be efficient in detecting a few micron of wear and cutting edge loss by chipping along the whole cutting edge.

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Image Fidelity Assessment Using the Edge Histogram Descriptor of MPEG-7

  • Won, Chee-Sun
    • ETRI Journal
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    • v.29 no.5
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    • pp.703-705
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    • 2007
  • An image fidelity assessment using the edge histogram descriptor (EHD) of MPEG-7 is presented. Neither additional data nor fragile watermarking is needed, and there is no need to access the original image as a reference. Only the EHDs of the original image and the received image are required. The peak signal-to-noise ratio (PSNR) obtained by comparing the EHD extracted from the received image and that of the original image is used to assess the noise level of the received image. Experimental results show that the PSNRs calculated from the conventional pixel-to-pixel gray level and from the proposed bin-to-bin EHD maintain a proportional relationship. This implies that the EHD can be used instead of image data for the image fidelity assessments.

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Edge Preserving Image Compression with Weighted Centroid Neural Network (신경망에 의한 테두리를 보존하는 영상압축)

  • 박동철;우영준
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.10B
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    • pp.1946-1952
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    • 1999
  • A new image compression method to preserve edge characteristics in reconstructed images using an unsupervised learning neural is proposed in this paper. By the unsupervised competitive learning which generalizes previously proposed Centroid Neural Network(CNN) algorithm with the geometric characteristics of edge area and statistical characteristics of image data, more codevectors are allocated in the edge areas to provide the more accurate edges in reconstructed image. Experimental results show that the proposed method gives improved edge in reconstructed images when compared with SOM, Modified SOM and M/R-CNN.

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A Potts Automata algorithm for Edge detection (Potts Automata를 이용한 영상의 에지 추출)

  • Lee, Seok-Ki;Kim, Seok-Tae;Cho, Sung-Jin
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.10a
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    • pp.767-770
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    • 2001
  • Edge detection is one of issues with essential importance in the area of image process. An edge in image is a boundary or contour which a significant change occurs in image intensity. In the paper, we process edge detection algorithms which are based on Potts automata. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. If Potts Automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose a Potts Automata technique for detecting edge. Based on the experimental results we discuss the advantage and efficiency.

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Speckle Noise Reduction with Morphological Adaptive Median Filtering Based on Edge Preservation

  • Jung, Eun Suk;Ryu, Conan K.R.;Hur, Chang Wu;Sun, Mingui
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.329-332
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    • 2009
  • Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise. As the result the proposed method enhances the image to about 20% in comparison with Winer filter by Edge Preservation Index and PSNR.

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