• Title/Summary/Keyword: 에지영역

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Vehicle number detection using histogram and probability (히스토그램과 확률을 이용한 차량 번호 검출 방법)

  • Kim, HyoYeon;Jung, DoWook;Choi, HyungIl
    • Proceedings of the Korea Contents Association Conference
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    • 2015.05a
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    • pp.307-308
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    • 2015
  • 자동차 번호판의 문자를 검출하기 위한 과정 중 그림자가 있는 후면 번호판을 이진화하는 방법을 제안한다. 대부분의 경우 차량구조에 의한 그림자 발생이 문자를 검출하는데 오류를 발생시킨다. 이를 해결하기 위해 그림자 영역과 아닌 영역의 경계를 검출해야 한다. 하지만, 기존 방법은 히스토그램에서 세 개의 영역사이에 있는 임계값 2개를 수동으로 결정해야 되는 점과 현재번호판의 색상인 흰색 바탕에 검은 문자에 적용하면 문자 영역의 그림자 경계선 검출이 모호하다는 단점이 있다. 본 논문에서는 이 문제를 해결하기 위하여 슬라이딩 윈도우를 이용한 히스토그램과 탐색하는 픽셀의 좌, 우 픽셀들을 스캔하여 연결되지 않은 에지를 찾아 그림자 경계선 에지를 연결하는 방법을 제안한다.

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Segmentation of Brain Image Using Multi-threshold and Vectorgram (Multi-threshold와 Vectorgram을 이 강한 Brain 영상 분할)

  • 이병일;최흥국
    • Proceedings of the Korea Multimedia Society Conference
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    • 2000.11a
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    • pp.262-265
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    • 2000
  • 영상에서의 경계선추출은 영상의 강도의 변화를 이용한 경계영역의 가시화 기법이므로 gray level 영상이 가지는 강도를 이용하여 에지를 찾을 수 있다. 뇌 영상에는 MRI 영상과 같이 해부학적인 정보가 큰 영상과, PET 영상같이 perfusion으로 분석해야 할 영상이 있는데 그 경계가 뚜렷한 MRI 영상과 달리 PET 뇌 영상은 영상의 특성상 경계영역의 구분이 모호한 실정이다. 본 논문에서는 이러한 영상의 특성에 따라 뇌 영상에서 영상 강도에 대해 등분할을 한 후 vectorgram에서 magnitude의 영역을 선택하여 영상을 분할 하였다. 그리고 PET 와 MRI영상과 현미경 영상에 대한 결과를 비교하였다. Vertcrgram은 에지정보를 가지는 영상에 대해 벡터요소를 그래프화 한 것으로 방향성에 대한 평가를 통해 영역 분할을 하였다. 이러한 PET 영상의 2차원 분할 방법은 3차원 PET 영상 분석에 응용될 수 있을 것이다.

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A study on Wavelet function for Improved Edge Detection Properties (개선된 에지검출 특성을 위한 웨이브렛 함수에 관한 연구)

  • Bae, Sang-Bum;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.197-200
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    • 2007
  • Edge representing the boundary between two regions with the large brightness difference in image includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge in according to duration time and the amplitude of brightness variation, and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

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Efficient Edge Detection in Noisy Images using Robust Rank-Order Test (잡음영상에서 로버스트 순위-순서 검정을 이용한 효과적인 에지검출)

  • Lim, Dong-Hoon
    • The Korean Journal of Applied Statistics
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    • v.20 no.1
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    • pp.147-157
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    • 2007
  • Edge detection has been widely used in computer vision and image processing. We describe a new edge detector based on the robust rank-order test which is a useful alternative to Wilcoxon test. Our method is based on detecting pixel intensity changes between two neighborhoods with a $r{\times}r$ window using an edge-height model to perform effectively on noisy images. Some experiments of our robust rank-order detector with several existing edge detectors are carried out on both synthetic images and real images with and without noise.

A Study on Edge Detection using Grey-Level Morphology (그레이 레벨 모폴로지를 이용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.687-690
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    • 2017
  • Edge detection is an important step in determining the performance of lane recognition, object and pattern detection, and so on. And much research has been done until now. Sobel, Prewitt, Roberts, and Canny edge detection algorithms are widely known. However, these algorithms are often judged to be a non-edge region when processing a smooth change in brightness value. Therefore, in this paper, edge detection algorithm using gray-level morphology using erosion, expansion, open and close in the mask area. is proposed.

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A Study on Wavelet Function for Improved Edge Detection Properties (개선된 에지검출 특성을 위한 웨이브렛 함수에 관한 연구)

  • Bae, Sang-Bum;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.6
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    • pp.1156-1161
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    • 2007
  • Edge representing the boundary between two regions with the large briskness difference in mage includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge according to duration time and the amplitude of brightness variation and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

A Wavelet-based Adaptive Image Watermarking Using Edge Table (영상의 에지 특성을 고려한 웨이블릿 기반의 적응적인 워터마킹 기법)

  • Lee Jae-Hyuk;Moon Ho-Seok;Park Sang-Sung;Jang Dong-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.2 s.40
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    • pp.53-63
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    • 2006
  • A discrete wavelet transform(DWT)-based image watermarking algorithm is proposed in this paper, the proposed method decompose the original image into four subsampled images. Subsampled images are transformed by 2 level DWT, respectively. The proposed method embeds the watermark into one of the subsampled DWT images using edge table that represents dege characteristics of the original image. Without an original image, a watermark is extracted through comparison one subsampled DWT image inserted the watermark with the rest of the submapled DWT images. many exiting methodes do not adequately estimate edge regions where intensities are changed abruptly. The proposed method address with an edge table. Also, even if the watermark is embedded into a low frequency area, our method preserves the image quality. The vality of the proposed method is demonstrated through the PSNR test and subjective image quality that human eyes feel.

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Medial Axis Detection of Stripes Using LoG Scale-Space (LoG Scale-Space를 이용한 라인의 중심축 검출)

  • Byun, Ki-Won;Nam, Ki-Gon;Joo, Jae-Heum
    • Journal of the Institute of Convergence Signal Processing
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    • v.11 no.3
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    • pp.183-188
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    • 2010
  • In this paper we propose a detection method of the medial axis of the continuous stripes on the LoG scale-space. Our method detects the medial axis of continuous stripes iteratively by varying the scale of LoG operator. Small-scale LoG operator detects two +/- pole pairs centered on the edge positions of stripe by the zero-crossing detection. The more increase the scale of LoG scale-space, the more close two poles to the medial axis of stripe. The medial axis of continuous stripe is the position where two poles is overlapped. The proposed method detected robustly the medial axis of continuous stripes stronger than the thinning methods used to binary image.

An Efficient Spatial Error Concealment Technique Using Adaptive Edge-Oriented Interpolation (적응적 방향성 보간을 이용한 효율적인 공간적 에러 은닉 기법)

  • Park, Sun-Kyu;Kim, Won-Ki;Jeong, Je-Chang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.5C
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    • pp.487-495
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    • 2007
  • When error occurs during the network transmission of the image, the quality of the restored image is very serious. Therefore to maintain the received image quality, the error concealment technique is necessary. This paper presents an efficient spatial error concealment method using adaptive edge-oriented interpolation. It deals with errors on slice level. The proposed method uses boundary matching method having 2-step processes. We divide error block into external and internal region, adaptively restore each region. Because this method use overall as well as local edge characteristics, it preserves edge continuity and texture feature. The proposed technique reduces the complexity and provide better reconstruction quality for damaged images than the previous methods.

Extraction of Text Alignment by Tensor Voting and its Application to Text Detection (텐서보팅을 이용한 텍스트 배열정보의 획득과 이를 이용한 텍스트 검출)

  • Lee, Guee-Sang;Dinh, Toan Nguyen;Park, Jong-Hyun
    • Journal of KIISE:Software and Applications
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    • v.36 no.11
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    • pp.912-919
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    • 2009
  • A novel algorithm using 2D tensor voting and edge-based approach is proposed for text detection in natural scene images. The tensor voting is used based on the fact that characters in a text line are usually close together on a smooth curve and therefore the tokens corresponding to centers of these characters have high curve saliency values. First, a suitable edge-based method is used to find all possible text regions. Since the false positive rate of text detection result generated from the edge-based method is high, 2D tensor voting is applied to remove false positives and find only text regions. The experimental results show that our method successfully detects text regions in many complex natural scene images.