• Title/Summary/Keyword: Canny Edge Detection

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A New Depth and Disparity Visualization Algorithm for Stereoscopic Camera Rig

  • Ramesh, Rohit;Shin, Heung-Sub;Jeong, Shin-Il;Chung, Wan-Young
    • Journal of information and communication convergence engineering
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    • v.8 no.6
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    • pp.645-650
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    • 2010
  • In this paper, we present the effect of binocular cues which plays crucial role for the visualization of a stereoscopic or 3D image. This study is useful in extracting depth and disparity information by image processing technique. A linear relation between the object distance and the image distance is presented to discuss the cause of cybersickness. In the experimental results, three dimensional view of the depth map between the 2D images is shown. A median filter is used to reduce the noises available in the disparity map image. After the median filter, two filter algorithms such as 'Gabor' filter and 'Canny' filter are tested for disparity visualization between two images. The 'Gabor' filter is to estimate the disparity by texture extraction and discrimination methods of the two images, and the 'Canny' filter is used to visualize the disparity by edge detection of the two color images obtained from stereoscopic cameras. The 'Canny' filter is better choice for estimating the disparity rather than the 'Gabor' filter because the 'Canny' filter is much more efficient than 'Gabor' filter in terms of detecting the edges. 'Canny' filter changes the color images directly into color edges without converting them into the grayscale. As a result, more clear edges of the stereo images as compared to the edge detection by 'Gabor' filter can be obtained. Since the main goal of the research is to estimate the horizontal disparity of all possible regions or edges of the images, thus the 'Canny' filter is proposed for decipherable visualization of the disparity.

Detecting Boundaries between Different Color Regions in Color Codes

  • Kwon B. H.;Yoo H. J.;Kim T. W.
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.846-849
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    • 2004
  • Compared to the bar code which is being widely used for commercial products management, color code is advantageous in both the outlook and the number of combinations. And the color code has application areas complement to the RFID's. However, due to the severe distortion of the color component values, which is easily over $50{\%}$ of the scale, color codes have difficulty in finding applications in the industry. To improve the accuracy of recognition of color codes, it'd better to statistically process an entire color region and then determine its color than to process some samples selected from the region. For this purpose, we suggest a technique to detect edges between color regions in this paper, which is indispensable for an accurate segmentation of color regions. We first transformed RGB color image to HSI and YIQ color models, and then extracted I- and Y-components from them, respectively. Then we performed Canny edge detection on each component image. Each edge image usually had some edges missing. However, since the resulting edge images were complementary, we could obtain an optimal edge image by combining them.

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Multiresolution Edge Detection Technique (다해상도 에지 검출 기법)

  • 박덕준;박래홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.28B no.12
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    • pp.51-58
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    • 1991
  • In this paper, we propose a multiresolution edge detection method which selects the edge detection window size and scale automatically by using the local variance information as an edgeness measure of a region. The mode of the local variance distribution which is calculated over the (2p + 1) x (2p + 1) windows is used to determine the resolution of the given pixel and the edge operator with different scale can be applied to the pixel depending on its resolution. The combination of the resolution determination scheme with the conventional Canny and LOG edge detectors gives the proposed multiresolution edge detection schemes. The effectness of the proposed schemes is shown via computer simulation.

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A Study on Edge Detection using Directional Mask in Impulse Noise Image (임펄스 잡음 영상에서 방향성 마스크를 이용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Institute of Convergence Signal Processing
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    • v.15 no.4
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    • pp.135-140
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    • 2014
  • As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

Lane Detection Using Gaussian Function Based RANSAC (가우시안 함수기반 RANSAC을 이용한 차선검출 기법)

  • Choi, Yeongyu;Seo, Eunyoung;Suk, Soo-Young;Park, Ju H.;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.13 no.4
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    • pp.195-204
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    • 2018
  • Lane keeping assist and departure prevention system are the key functions of ADAS. In this paper, we propose lane detection method which uses Gaussian function based RANSAC. The proposed method consists mainly of IPM (inverse perspective mapping), Canny edge detector, and Gaussian function based RANSAC (Random Sample Consensus). The RANSAC uses Gaussian function to extract the parameters of straight or curved lane. The proposed RANSAC is different from the conventional one, in the following two aspects. One is the selection of sample with different probability depending on the distance between sample and camera. Another is the inlier sample score that assigns higher weights to samples near to camera. Through simulations, we show that the proposed method can achieve good performance in various of environments.

Vision Processing for Precision Autonomous Landing Approach of an Unmanned Helicopter (무인헬기의 정밀 자동착륙 접근을 위한 영상정보 처리)

  • Kim, Deok-Ryeol;Kim, Do-Myoung;Suk, Jin-Young
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.1
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    • pp.54-60
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    • 2009
  • In this paper, a precision landing approach is implemented based on real-time image processing. A full-scale landmark for automatic landing is used. canny edge detection method is applied to identify the outside quadrilateral while circular hough transform is used for the recognition of inside circle. Position information on the ground landmark is uplinked to the unmanned helicopter via ground control computer in real time so that the unmanned helicopter control the air vehicle for accurate landing approach. Ground test and a couple of flight tests for autonomous landing approach show that the image processing and automatic landing operation system have good performance for the landing approach phase at the altitude of $20m{\sim}1m$ above ground level.

Identification of 5-Jung-color and 5-Kan-color In Video (비디오에서 오정색과 오간색 식별)

  • Shin, Seong-Yoon;Pyo, Seong-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.1
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    • pp.103-109
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    • 2010
  • As color was used for formative language since a human activity was beginning, all the symptoms in the world that the human eye can see is present. In this paper, we identify Korea traditional color harmony for extracted key frames from scene change detection. Traditional color is classified as 5-Jung-color and 5-Kan-color, and determine whether to harmony. Red, blue, yellow, black, and white, called 5-Jung-color and pink, blue, purple, sulfur, and green, called the 5-Kan-color was identified. First, we extract edge using Canny algorithm. And, we are labeling and clustering colors around the edge. Finally, we identify the traditional color using identification method of traditional color harmony. The proposed study in this paper has been proven through experiments.

Ileus Detection by Using Edge Information and Hough Transform (에지 정보와 Hough Transform을 이용한 장폐색 영역 검출)

  • Lee, Hae Ill;Kim, Baek Cheon;Kim, Hyun Woo;Park, Seung Ik;Kim, Kwang Beak
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.488-490
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    • 2017
  • 본 논문에서는 장폐색 영역을 추출하는 방법을 제안한다. 제안된 방법은 Canny Edge Detector을 이용하여 X-ray 영상에서 객체들의 에지를 추출한다. 검출된 객체 에지들에서 장폐색의 영역이 형태학적으로 수평적으로 평평하다는 특징을 이용하기 위해서 Hough transform을 적용하여 수평적으로 평평한 영역을 가진 객체들을 추출하고, 추출된 객체들을 장폐색 영역으로 검출한다. 제안된 추출 방법을 25개의 장폐색 X-ray 영상을 대상으로 실험한 결과, 제안된 방법에서는 19개 대장 장폐색 영상에서는 모두 추출되었으나 6개의 소장 장폐색 영상에서는 추출에 실패하였다.

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An Improved Level Set Method to Image Segmentation Based on Saliency

  • Wang, Yan;Xu, Xianfa
    • Journal of Information Processing Systems
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    • v.15 no.1
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    • pp.7-21
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    • 2019
  • In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

Edge detection and noise removal algorithm (외곽선 검출 및 잡음 제거 알고리즘)

  • Moon, Woo-Hyeok;Jung, Si-Hun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.945-947
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    • 2021
  • Canny Edge Detection은 필터와 방향벡터를 이용한 대표적인 외곽선 추출 알고리즘으로서 대부분의 외곽선 추출 연구에서 이를 변형하여 사용한다. 그러나 본 논문에서는 외곽선 추출의 전처리 과정으로서 이미지에서의 잡음을 제거하는 알고리즘과 이를 바탕으로 외곽선을 더욱 효율적으로 추출할 수 있는 독창적인 알고리즘을 제시한다.