• Title/Summary/Keyword: Canny detection

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A Study on a Lane Detection and Tracking Algorithm Using B-Snake (B-Snake를 이용한 차선 검출 및 추적 알고리즘에 관한 연구)

  • Kim, Deok-Rae;Moon, Ho-Sun;Kim, Yong-Deak
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.4 s.304
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    • pp.21-30
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    • 2005
  • In this paper, we propose lane detection and trackinB algerian using B-Snake as robust algorithm. One of chief virtues of Lane detection algorithm using B-Snake is that it is possible to specify a wider range of lane structure because B-Spline conform an arbitrary shape by control point set and that it doesn't use any camera parameter. Using a robust algorithm called CHVEP, we find the vanishing point, width of lane and mid-line of lane because of the perspective parallel line and then we can detect the both side of lane mark using B-snake. To demonstrate that this algorithm is robust against noise, shadow and illumination variations in road image, we tested this algorithm about various image divided by weather-fine, rainy and cloudy day. The percentage of correct lane detection is over 95$\%$.

Color Code Detection and Recognition Using Image Segmentation Based on k-Means Clustering Algorithm (k-평균 클러스터링 알고리즘 기반의 영상 분할을 이용한 칼라코드 검출 및 인식)

  • Kim, Tae-Woo;Yoo, Hyeon-Joong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.6
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    • pp.1100-1105
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    • 2006
  • Severe distortions of colors in the obtained images have made it difficult for color codes to expand their applications. To reduce the effect of color distortions on reading colors, it will be more desirable to statistically process as many pixels in the individual color region as possible, than relying on some regularly sampled pixels. This process may require segmentation, which usually requires edge detection. However, edges in color codes can be disconnected due tovarious distortions such as zipper effect and reflection, to name a few, making segmentation incomplete. Edge linking is also a difficult process. In this paper, a more efficient approach to reducing the effect of color distortions on reading colors, one that excludes precise edge detection for segmentation, was obtained by employing the k-means clustering algorithm. And, in detecting color codes, the properties of both six safe colors and grays were utilized. Experiments were conducted on 144, 4M-pixel, outdoor images. The proposed method resulted in a color-code detection rate of 100% fur the test images, and an average color-reading accuracy of over 99% for the detected codes, while the highest accuracy that could be achieved with an approach employing Canny edge detection was 91.28%.

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A Real-Time Inspection System for Digital Textile Printing (디지털 프린팅을 위한 실시간 직물 결점 검출 시스템)

  • Kim, Kyung-Joon;Lee, Chae-Jung;Park, Yoon-Cheol;Kim, Joo-Yong
    • Textile Coloration and Finishing
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    • v.20 no.1
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    • pp.48-56
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    • 2008
  • A real-time inspection system has been developed by combining CCD based image processing algorithm and a standard lighting equipment. The system was tested for defective fabrics showing nozzle contact scratch marks, which are one of the frequently occurring defects. Two algorithms used were compared according to both their processing time and detection rate. First algorithm (algorithm A) was based on morphological image processing such as dilation and opening for effective treatment of defective printing areas while second one (algorithm B) mainly employs well-defined edge detection technique based on canny detector and Zermike moment. It was concluded' that although both algorithms were quite successful, algorithm B showed relatively consistent performance than algorithm A in detecting complex patterns.

The Development of a Marker Detection Algorithm for Improving a Lighting Environment and Occlusion Problem of an Augmented Reality (증강현실 시스템의 조명환경과 가림현상 문제를 개선한 마커 검출 알고리즘 개발)

  • Lee, Gyeong Ho;Kim, Young Seop
    • Journal of the Semiconductor & Display Technology
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    • v.11 no.1
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    • pp.79-83
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    • 2012
  • We use adaptive method and determine threshold coefficient so that the algorithm could decide a suitable binarization threshold coefficient of the image to detecting a marker; therefore, we solve the light influence on the shadow area and dark region. In order to improve the speed for reducing computation we created Integral Image. The algorithm detects an outline of the image by using canny edge detection for getting damage or obscured markers as it receives the noise removed picture. The strength of the line of the outline is extracted by Hough transform and it extracts the candidate regions corresponding to the coordinates of the corners. Markers extracted using the equation of a straight edge to find the coordinates. By using the equation of straight the algorithm finds the coordinates the corners. of extracted markers. As a result, even if all corners are obscured, the algorithm can find all of them and this was proved through the experiment.

A Study on Finding the Rail Space in Elevators Using Matched Filter

  • Song, Myong-Lyol
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.6
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    • pp.57-65
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    • 2019
  • In this paper, we study on finding the rail space in elevators by analyzing each image captured with CCD camera. We propose a method that applies one-dimensional matched filter to the pixels of a selected search space in the vertical line at a horizontal position and decides the position with the thickness of the space being represented by a black thick line in captured images. The pattern similarity representing how strongly the associated image pixels resemble with the thick line is defined and calculated with respect to each position along the vertical line of pixels. The position and thickness of the line are decided from the point having the maximum in pattern similarity graph. In the experiments of the proposed method under different illuminational conditions, it is observed that all the pattern similarity graphs show similar shape around door area independent of the conditions and the method can effectively detect the rail space if the rails are illuminated with even weak light. The method can be used for real-time embedded systems because of its simple algorithm, in which it is implemented in simple structure of program with small amount of operations in comparison with the conventional approaches using Canny edge detection and Hough transform.

Identification of Vehicle Using Edge Detection (에지 검출에 의한 차량 식별)

  • Shin, SY;Kim, DK;Lee, CW;Lee, HC;Lee, TW;Park, KH
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.382-383
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    • 2016
  • Canny edge detection of the image is composed of four kinds of Gaussian filter, gradient calculation, Non-maximum suppression, and Hypothesis Thresholding. Feature is the ratio between the vehicle body, the windows, and the wheels obtained from the edge image. Features that make the proportion of these vehicles are different for each respective model. We have identified by application of this algorithm where only a small vehicle.

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A method for underwater image analysis using bi-dimensional empirical mode decomposition technique

  • Liu, Bo;Lin, Yan
    • Ocean Systems Engineering
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    • v.2 no.2
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    • pp.137-145
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    • 2012
  • Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

Force Shading using Height Map for Virtual Tak-bon Simulation (가상 탁본 시뮬레이션의 Height Map을 이용한 힘 쉐이딩)

  • Park, Ye-Seul;Park, Jin-Ah
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.590-594
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    • 2008
  • 근래에 인간과 컴퓨터의 상호작용을 통하여 사용자에게 직관적인 정보를 제공하는 기술들이 발전하고 있으며, 그래픽 기술의 비실사 렌더링을 이용한 미술 기법을 사실감 있게 가상 체험하기 위한 어플리케이션이 제안되고 있다. 본 논문은 미술 기법 중 방망이를 이용한 탁본 기법을 가상의 환경에서 모사하기 위해 탁본의 방망이를 통한 힘 쉐이딩을 새롭게 고안하여 제안한다. 햅틱 커서의 포인트와는 달리 탁본 방망이의 면적이 접촉하는 부분에서 생기는 문제점을 해결하기 위하여 Height map으로 사용된 Canny Edge Detection 이미지를 통해 Height map을 부분적으로 재 정의하고 힘의 계산에 적용하여 충돌된 방망이의 힘 쉐이딩을 가능하게 하는 것이 원리이다. 그래픽 렌더링 효과와 함께 실시간으로 사용자에게 햅틱 장치를 이용하여 촉감 정보를 전달함으로써 다양한 미술 교육적 효과를 체험할 수 있는 방안을 제공할 것으로 기대된다.

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Automatic Mask Generation for 3D Makeup Simulation (3차원 메이크업 시뮬레이션을 위한 자동화된 마스크 생성)

  • Kim, Hyeon-Joong;Kim, Jeong-Sik;Choi, Soo-Mi
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.397-402
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    • 2008
  • 본 논문에서는 햅틱 인터랙션 기반의 3차원 가상 얼굴 메이크업 시뮬레이션에서 메이크업 대상에 대한 정교한 페인팅을 적용하기 위한 자동화된 마스크 생성 방법을 개발한다. 본 연구에서는 메이크업 시뮬레이션 이전의 전처리 과정에서 마스크를 생성한다. 우선, 3차원 스캐너 장치로부터 사용자의 얼굴 텍스쳐 이미지와 3차원 기하 표면 모델을 획득한다. 획득된 얼굴 텍스쳐 이미지로부터 AdaBoost 알고리즘, Canny 경계선 검출 방법과 색 모델 변환 방법 등의 영상처리 알고리즘들을 적용하여 마스크 대상이 되는 주요 특정 영역(눈, 입술)들을 결정하고 얼굴 이미지로부터 2차원 마스크 영역을 결정한다. 이렇게 생성된 마스크 영역 이미지는 3차원 표면 기하 모델에 투영되어 최종적인 3차원 특징 영역의 마스크를 레이블링하는데 사용된다. 이러한 전처리 과정을 통하여 결정된 마스크는 햅틱 장치와 스테레오 디스플레이기반의 가상 인터페이스를 통해서 자연스러운 메이크업 시뮬레이션을 수행하는데 사용된다. 본 연구에서 개발한 방법은 사용자에게 전처리 과정에서의 어떠한 개입 없이 자동적으로 메이크업 대상이 되는 마스크 영역을 결정하여 정교하고 손쉬운 메이크업 페인팅 인터페이스를 제공한다.

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Realtime Face Recognition using the Skin Color and Information of Face (얼굴의 피부색과 정보를 이용한 실시간 얼굴 인식)

  • Lee, Min-Ho;Hwang, Dae-Dong;Choi, Hyung-Il
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2009.01a
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    • pp.173-176
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    • 2009
  • 본 논문에서는 피부색 정보와 눈, 입의 위치를 찾아 실시간으로 얼굴을 인식하는 랩을 제안한다. 먼저 노이즈를 제거하여 얼굴 후보 영역을 지정한다. 지정된 얼굴 후보 영역에서 눈과 입을 찾고, 찾은 눈과 입 사이의 영역에서 에지를 탐색하여 코의 존재 유무를 검증하고 이를 바탕으로 얼굴인지 판단하는 절차를 따른다. 제안한 기법은 피부색 검출을 위해 YCbCr 을 이용하여 피부 영역을 찾고 지정한 피부 영역에서 노이즈를 제거한 후, Eye Map의 EyeMapC 연산을 통해 눈을 Lip Map을 통해 입을 찾는다. 찾아낸 눈과 입의 사이의 영역에서 Canny Edge 연산을 수행하여 코의 존재 유무를 판단하여 최종적인 얼굴 영역을 판별하는 방법을 제안한다.

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