• Title/Summary/Keyword: Edge extraction

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Extraction of Car License Plate Region Using Histogram Features of Edge Direction (에지 영상의 방향성분 히스토그램 특징을 이용한 자동차 번호판 영역 추출)

  • Kim, Woo-Tae;Lim, Kil-Taek
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.3
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    • pp.1-14
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    • 2009
  • In this paper, we propose a feature vector and its applying method which can be utilized for the extraction of the car license plate region. The proposed feature vector is extracted from direction code histogram of edge direction of gradient vector of image. The feature vector extracted is forwarded to the MLP classifier which identifies character and garbage and then the recognition of the numeral and the location of the license plate region are performed. The experimental results show that the proposed methods are properly applied to the identification of character and garbage, the rough location of license plate, and the recognition of numeral in license plate region.

License Plate Recognition Using The Morphological Size Distribution Functions (형태학적 크기 분포 함수를 이용한 자동차 번호판 인식)

  • 차상혁;김주영;고광식
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.455-458
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    • 2001
  • In this paper, a new license plate recognition method using the morphological size distribution functions and color images is proposed. The proposed method consists of two steps. The first step is license plate extraction process using the plate color and step edge information in the license plate. The second step is the extraction of character feature vectors using the morphological size distribution functions and character recognition process using the MLP(multilayer perceptron). By the use of morphological size distributions functions, the error that may occur during the character region extraction process is lessened and the recognition performances are improved by the decrease of feature vector dimension.

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Salient Object Extraction from Video Sequences using Contrast Map and Motion Information (대비 지도와 움직임 정보를 이용한 동영상으로부터 중요 객체 추출)

  • Kwak, Soo-Yeong;Ko, Byoung-Chul;Byun, Hye-Ran
    • Journal of KIISE:Software and Applications
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    • v.32 no.11
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    • pp.1121-1135
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    • 2005
  • This paper proposes a moving object extraction method using the contrast map and salient points. In order to make the contrast map, we generate three-feature maps such as luminance map, color map and directional map and extract salient points from an image. By using these features, we can decide the Attention Window(AW) location easily The purpose of the AW is to remove the useless regions in the image such as background as well as to reduce the amount of image processing. To create the exact location and flexible size of the AW, we use motion feature instead of pre-assumptions or heuristic parameters. After determining of the AW, we find the difference of edge to inner area from the AW. Then, we can extract horizontal candidate region and vortical candidate region. After finding both horizontal and vertical candidates, intersection regions through logical AND operation are further processed by morphological operations. The proposed algorithm has been applied to many video sequences which have static background like surveillance type of video sequences. The moving object was quite well segmented with accurate boundaries.

Extracting optimal moving patterns of edge devices for efficient resource placement in an FEC environment (FEC 환경에서 효율적 자원 배치를 위한 엣지 디바이스의 최적 이동패턴 추출)

  • Lee, YonSik;Nam, KwangWoo;Jang, MinSeok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.1
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    • pp.162-169
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    • 2022
  • In a dynamically changing time-varying network environment, the optimal moving pattern of edge devices can be applied to distributing computing resources to edge cloud servers or deploying new edge servers in the FEC(Fog/Edge Computing) environment. In addition, this can be used to build an environment capable of efficient computation offloading to alleviate latency problems, which are disadvantages of cloud computing. This paper proposes an algorithm to extract the optimal moving pattern by analyzing the moving path of multiple edge devices requiring application services in an arbitrary spatio-temporal environment based on frequency. A comparative experiment with A* and Dijkstra algorithms shows that the proposed algorithm uses a relatively fast execution time and less memory, and extracts a more accurate optimal path. Furthermore, it was deduced from the comparison result with the A* algorithm that applying weights (preference, congestion, etc.) simultaneously with frequency can increase path extraction accuracy.

Moving Object Contour Detection Using Spatio-Temporal Edge with a Fixed Camera (고정 카메라에서의 시공간적 경계 정보를 이용한 이동 객체 윤곽선 검출 방법)

  • Kwak, Jae-Ho;Kim, Whoi-Yul
    • Journal of Broadcast Engineering
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    • v.15 no.4
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    • pp.474-486
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    • 2010
  • In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

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.

Edge Extraction Using Central Moments (Central Moments를 이용한 경계선 검출)

  • Kim, Hark-Sang;Kang, Young-Mo;Park, Kil-Houm;Lee, Kwang-Ho;Ha, Yeong-Ho
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.25 no.10
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    • pp.1244-1251
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    • 1988
  • Edge is one of the primitive features of an image and is widely used in image classification and analysis. New edge extration methods using central moments are presented and show various characteristics according to the order of moment, definition of both random variables and probability density functions. The proposed methods use the integral of differences between local mean and pixels in the window whereas most of conventional edge operators use only differential concepts. This gives good noise immunity and extracts fine edges.

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Feature Extraction for Scene Change Detection in an MPEG Video Sequence (장면 전환 검출을 위한 MPEG 비디오 시퀀스로부터 특징 요소 추출)

  • 최윤석;곽영경;고성제
    • Journal of Broadcast Engineering
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    • v.3 no.2
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    • pp.127-137
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    • 1998
  • In this paper, we propose the method of extracting edge information from MPEG video sequences for the detection of scene changes. In a the proposed method, five significant AC coefficients of each MPEG block are utilized to obtain edge images from the MPEG video. AC edge images obtained by the proposed scheme not only produce better object boundary information than conventional methods using only DC coefficients, but also can reduce the boundary effects produced by DC-based. Since the AC edge image contains the content information of each frame, it can be effectively utilized for the detection of scene change as well as the content-based video query. Experimental results show that the proposed method can be effectively utilized for the detection of scene changes.

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FINE SEGMENTATION USING GEOMETRIC ATTRACTION-DRIVEN FLOW AND EDGE-REGIONS

  • Hahn, Joo-Young;Lee, Chang-Ock
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.11 no.2
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    • pp.41-47
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    • 2007
  • A fine segmentation algorithm is proposed for extracting objects in an image, which have both weak boundaries and highly non-convex shapes. The image has simple background colors or simple object colors. Two concepts, geometric attraction-driven flow (GADF) and edge-regions are combined to detect boundaries of objects in a sub-pixel resolution. The main strategy to segment the boundaries is to construct initial curves close to objects by using edge-regions and then to make a curve evolution in GADF. Since the initial curves are close to objects regardless of shapes, highly non-convex shapes are easily detected and dependence on initial curves in boundary-based segmentation algorithms is naturally removed. Weak boundaries are also detected because the orientation of GADF is obtained regardless of the strength of boundaries. For a fine segmentation, we additionally propose a local region competition algorithm to detect perceptible boundaries which are used for the extraction of objects without visual loss of detailed shapes. We have successfully accomplished the fine segmentation of objects from images taken in the studio and aphids from images of soybean leaves.

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Extraction of Tongue Region using Graph and Geometric Information (그래프 및 기하 정보를 이용한 설진 영역 추출)

  • Kim, Keun-Ho;Lee, Jeon;Choi, Eun-Ji;Ryu, Hyun-Hee;Kim, Jong-Yeol
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.11
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    • pp.2051-2057
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    • 2007
  • In Oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive and widely used in Oriental medicine. However, tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue is inevitable but difficult since the colors of a tongue, lips and skin in a mouth are similar. The proposed method includes preprocessing, graph-based over-segmentation, detecting positions with a local minimum over shading, detecting edge with color difference and estimating edge geometry from the probable structure of a tongue, where preprocessing performs down-sampling to reduce computation time, histogram equalization and edge enhancement. A tongue was segmented from a face image with a tongue from a digital tongue diagnosis system by the proposed method. According to three oriental medical doctors' evaluation, it produced the segmented region to include effective information and exclude a non-tongue region. It can be used to make an objective and standardized diagnosis.