• Title/Summary/Keyword: 에지 방향정보

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A Study on Game Character Classification Based on Texture and Edge Orientation Feature (질감 및 에지 방향 특징에 기반한 게임 캐릭터 분류에 관한 연구)

  • Park, Chang-Min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.6
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    • pp.1318-1324
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    • 2012
  • This paper proposes a novel method for Game character classification based on texture and edge orientation feature. The character dose not move(NPC) and move the character is classified. Classification of property within the character of straight line segments are used to extract features. First, the character inside edge feature extraction and then calculates EEDH, SSPD. The extracted attribute represents the energy of a particular direction. Thus, these properties were used to classify of NPC and Monster. The proposed method, the user can reduce the unnecessary time in the game.

A Study on Edge Detection using Modified Histogram Equalization (변형된 히스토그램 평활화를 적용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • 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.

Edge Feature Vector Extraction using Higher-Order Local Autocorrelation and Its Application in Image Retrieval (고차국소 자기상관함수를 이용한 에지 특징벡터의 생성과 유사이미지에의 적용)

  • 윤미진;오군석;김판구
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.562-564
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    • 2002
  • 본 논문에서는 자기상관함수의 국소적 특징을 사용하여 에지 특징을 추출한 후, 이를 이용해 유사이미지를 검색하는 방법을 제시한다. 자기상관함수의 국소적 특징을 이용하여 이미지를 검색할 경우 크기, 밝기, 색상등과 같은 이미지 요소가 서로 다를 경우에도 영향을 받지 않고 에지 특징정보를 추출해 낼 수 있다. 이는 얻어진 에지 특징을 이미지 크기와 고차 국소 자기상관함수의 변위에 의해 변하지 않도록 정규화를 하고, 동일 이미지에 대해 밝기가 조금 달라지면 검색효율이 떨어지는 점을 해결하기 위해 거리척도로서 방향여현거리(direction cosine distance)를 이용함으로써 가능하다. 이렇게 추출된 특징벡터를 자기조직화 맵에 의하여 클러스터링하고, 유사이미지 검색의 효율성을 비교해본 결과, 본 논문에서 제시한 방법을 사용하여 검색한 경우 재현율이 기존의 방법에 비해서 비교적 높은 수치를 나타냈다.

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Improved Method for Feature Extraction by Using Vallly-Line (골선을 이용한 지문영상의 특징점 추출 향상 기법)

  • 여인효;한상훈;조형제
    • Proceedings of the Korea Multimedia Society Conference
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    • 2003.05b
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    • pp.380-384
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    • 2003
  • 현재 정보의 가치가 높아짐에 따라 생체인식에 대한 연구가 많아지고 있다. 특히 지문에 대한 연구가 활발한데 기존의 융선을 이용한 특징점 추출이 아닌 지문에서 잡음이 적은 골선을 이용하고 에지 보존 평활화를 12방향각에 대해 적용함으로 보다 세밀한 에지 보존 평활화를 사용함으로 보다 정확한 특징점 추출의 방법을 제안한다.

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A Study on the Edge Detection using Variable Vector Depending on the Distribution of Gray-Level (밝기 분포도에 따라 가변 가능한 벡터를 이용한 에지 검출)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.130-132
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    • 2012
  • The use of visual media has been increased by development of contemporary society. To use these information of image, there are various methods of image processing. Edge detection which is one of those is technique to detect dramatically changing part of image brightness. Existing methods detect edge through mask which is composited by constant values. Because existing methods do not consider factor as location, direction of pixel in image, performance of edge detecting in insufficient. Therefore, an algorithm which is using variable vector for the variation of brightness in mask of $3{\times}3$ pixels is proposed.

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The Proposal of the Robust Fuzzy Wavelet Morphology Neural Networks Algorithm for Edge of Color Image (컬러 영상 에지에 강건한 퍼지 웨이브렛 형태학 신경망 알고리즘 제안)

  • Byun, Oh-Sung
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.53-62
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    • 2007
  • In this paper, it can propose that Fuzzy Wavelet Morphology Neural Networks for the edge detection algorithm with being robustly a unclear boundary parts by brightness difference and being less sensitivity on direction to be detected the edges of images. This is applying the Fuzzy Wavelet Morphology Operator which can be simple the image robustly without the loss of data to DTCNN Structure for improving defect which carrys out a lot of operation complexly. Also, this color image can segment Y image with YCbCr space color model which has a lossless feature information of edge boundary sides effectively. This paper can offer the simulation of color images of 50ea for the performance verification of the proposal algorithm.

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Two-sample Linear Rank Tests for Efficient Edge Detection in Noisy Images (잡음영상에서 효과적인 에지검출을 위한 이표본 선형 순위 검정법)

  • Lim Dong-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.4 s.42
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    • pp.9-15
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    • 2006
  • In this paper we propose Wilcoxon test, Median test and Van der Waerden test such as linear rank tests in two-sample location problem for detecting edges effectively in noisy images. These methods are based on detecting image intensity changes between two pixel neighborhoods using an edge-height model to perform effectively on noisy images. The neighborhood size used here is small and its shape is varied adaptively according to edge orientations. We compare and analysis the performance of these statistical edge detectors on both natural images and synthetic images with and without noise.

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Effective Line Detection of Steel Plates Using Eigenvalue Analysis (고유값 분석을 이용한 효과적인 후판의 직선 검출)

  • Park, Sang-Hyun;Kim, Jong-Ho;Kang, Eui-Sung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.7
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    • pp.1479-1486
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    • 2011
  • In this paper, a simple and robust algorithm is proposed for detecting straight line segments in a steel plate image. Line detection from a steel plate image is a fundamental task for analyzing and understanding of the image. The proposed algorithm is based on small eigenvalue analysis. The proposed approach scans an input edge image from the top left comer to the bottom right comer with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Before calculating the eigenvalue, each line segment is separated from the edge image where several line segments are overlapped to increase the accuracy of the line detection. Additionally, unnecessary line segments are eliminated by the number of pixels and the directional information of the detected line edges. The respects of the experiments emphasize that the proposed algorithm outperforms the existing algorithm which uses small eigenvalue analysis.

Extraction of Car Number Plate Based on Edge Projection (에지투영 기반의 자동차 번호판 영역 추출)

  • Kim, Dong-Wook;Kang, Jeong-Hyuck
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.6
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    • pp.261-268
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    • 2007
  • In this paper, We propose a new technique extract efficiently a car number plate based on edge projection. In order to obtain the region of car number plate, we use a motive that the luminance differences between the number plate background and characters. And, we introduce a projection technique to obtain character parts based on edge image. In vertical direction. we propose a shape matching method. Specially the new number plate standard has more characters than the old one in horizontal direction and, it is efficiently used to extract the number plate. Therefore, the proposed technique is useful to the new number plate standard. In simulation results. We have illustrated that our algorithm can recognize different number plates with a success ration of 90%.

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Anisotropic Diffusion based on Directions of Gradient (기울기 방향성 기반의 이방성 확산)

  • Kim, Hye-Suk;Kim, Gi-Hong;Yoon, Hyo-Sun;Lee, Guee-Sang
    • The Journal of the Korea Contents Association
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    • v.8 no.11
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    • pp.1-9
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    • 2008
  • Thanks to the multimedia technology development, it is possible to show image representations in high quality and to process images in various ways. Anisotropic diffusion as an effective diffusion filtering among many image preprocessing methods and postprocessing methods is used in reduction of speckle noises of ultrasound images, image restoration, edge detection, and image segmentation. However, the conventional anisotropic diffusion based on a cross-kernel causes the following problems. The problem is the concentration of edges in the vertical or horizontal directions. In this paper, a new anisotropic diffusion transform based on directions of gradient is proposed. The proposed method uses the eight directional square-kernel which is an expanded form of the cross-kernel. The proposed method is to select directions of small gradient based on square-kernel. Therefore, the range of proposed diffusion is selected adaptively according to the number of the directions of gradient. Experimental results show that the proposed method can decrease the concentration of edges in the vertical or horizontal directions, remove impulse noise. The image in high quality can be obtained as a result of the proposed method.