• Title/Summary/Keyword: Canny detection

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Improvement of Power Consumption of Canny Edge Detection Using Reduction in Number of Calculations at Square Root (제곱근 연산 횟수 감소를 이용한 Canny Edge 검출에서의 전력 소모개선)

  • Hong, Seokhee;Lee, Juseong;An, Ho-Myoung;Koo, Jihun;Kim, Byuncheul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.6
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    • pp.568-574
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    • 2020
  • In this paper, we propose a method to reduce the square root computation having high computation complexity in Canny edge detection algorithm using image processing. The proposed method is to reduce the number of operation calculating gradient magnitude using pixel's continuity using make a specific pattern instead of square root computation in gradient magnitude calculating operation. Using various test images and changing number of hole pixels, we can check for calculate match rate about 97% for one hole, and 94%, 90%, 88% when the number of hole is increased and measure decreasing computation time about 0.2ms for one hole, and 0.398ms, 0.6ms, 0.8ms when the number of hole is increased. Through this method, we expect to implement low power embedded vision system through high accuracy and a reduced operation number using two-hole pixels.

Progress of Edge Detection Using Mean Shift Algorithm (Mean Shift 알고리즘을 활용한 경계선 검출의 발전)

  • Jang, Dai-Hyun;Park, Sang-Joon;Park, Ki-Hong;Chung, Kyung-Taek;Hwang, Jae-Jeong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.10a
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    • pp.137-139
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    • 2011
  • 영상에서의 경계선 추출은 원 영상의 노이즈에 의해 크게 영향을 받는다. 따라서 먼저 그 노이즈들을 제거할만한 어떤 방법들이 필요하다. Mean Shift 알고리즘은 이러한 목적에 부합되는 유연한 함수로서, 별로 중요하지 않은 정보와 민감한 노이즈 부분을 점점 제거하는데 알맞다. 여기서는 Canny 알고리즘을 사용하여 중점으로 하는 영상에서의 윤곽선을 찾아낸다. 그리고 테스트 하고 이전의 유일한 Canny 알고리즘 보다 결과가 좋음을 알아낸다.

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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.

Needle Detection by using Morphological Operation and Line Segment Approximation (형태학적 연산과 선분 근사화를 이용한 침 검출)

  • Jang, Kyung-shik;Han, Soowhan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.12
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    • pp.2785-2791
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    • 2015
  • In this paper, neddle detection algorithm for the removal of needle stuck into skin in oriental clinic is presented. First, in the proposed method, potential candidate areas of each needle are selected by using the morphological open operation in a gray image, and the false candidates are removed by considering their area size. Next, edge points are extracted using canny edge detector in selected candidate areas, line segments are approximated using the edge points. Based on the direction of line segment and the distance between two line segments, two main line segments of the needle are extracted. The final verification of needle is accomplished by using the morphological analysis of these two line segments. In the experiments, the detection rate of proposed method reaches to 97.5% for the 16 images containing 119 needles.

Using Mean Shift Algorithm Enhance Edge Detection Effect (에지 추출 향상을 위한 Mean Shift 알고리즘의 이용)

  • Lei, Wang;Shin, Seong-Yoon;Rhee, Yang-Won
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2009.01a
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    • pp.211-214
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    • 2009
  • Edge detection always influenced by noise belong to the original image, therefore need use some methods to sort this issue, mean shift algorithm has the smooth function which suit for the edge detection purpose, so adopted to fade out the unimportant information, and the sensitive noise portions. After this section, use the Canny algorithm to pick up the contour of the objects we focus on, meanwhile select the Soble operator that has the orientation attribute to support the method work well. In final, take experiment and get the perfect result we wanted, make sure this method make sense and better than the sole Edge detection algorithm,

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Using mean shift and self adaptive Canny algorithm enhance edge detection effect (Mean Shift 알고리즘과 Canny 알고리즘을 이용한 에지 검출 향상)

  • Lei, Wang;Shin, Seong-Yoon;Rhee, Yang-Won
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2009.01a
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    • pp.207-210
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    • 2009
  • Edge detection is an important process in low level image processing. But many proposed methods for edge detection are not very robust to the image noise and are not flexible for different images. To solve the both problems, an algorithm is proposed which eliminate the noise by mean shift algorithm in advance, and then adaptively determine the double thresholds based on gradient histogram and minimum interclass variance, With this algorithm, it can fade out almost all the sensitive noise and calculate the both thresholds for different images without necessity to setup any parameter artificially, and choose edge pixels by fuzzy algorithm.

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Algorithm for Detecting PSD Boundary Invasion in Subway PSD using Image Processing (영상처리를 이용한 지하철 스크린 도어의 경계선 침범인식 알고리듬 연구)

  • Baek, Woon-Seok;Lee, Ha-Woon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.5
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    • pp.1051-1058
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    • 2018
  • This paper propose image processing algorithm to prevent safety accidents near by subway platform screen door(PSD). First, edges of the subway PSD images are detected and the boundary line between PSD and subway platform is detected to decide people's approach to the PSD using Hough transform. To do this, we draw the boundary line between the PSD and platform, to detect the boundary line and to decide the people's approach to the detected line is completely connected or not. Generally, edge is the basic characteristic of image; thus, edge detection is very important in image processing applications and computer vision area. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask, and morphological gradient from the structuring element of view and Canny edge detector are widely used. In this paper, we propose the detection algorithm about the people's approach to the subway PSD to prevent the safety accidents by using Canny edge detector and Hough transform and the computer simulation shows the results.

Comparison of Common Methods from Intertwined Application in Image Processing

  • Shin, Seong-Yoon;Lee, Hyun-Chang;Rhee, Yang-Won
    • Journal of information and communication convergence engineering
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    • v.8 no.4
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    • pp.405-410
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    • 2010
  • Image processing operations like smoothing and edge detection, and many more are very widely used in areas like Computer Vision. We classify the image processing domain as seven branches-image acquirement and output, image coding and compression, image enhancement and restoration, image transformation, image segmentation, image description, and image recognition and description. We implemented algorithms of gaussian smoothing, laplace sharpening, image contrast effect, image black and white effect, image fog effect, image bright and dark effect, image median filter, and canny edge detection. Such experimental results show the figures respectively.

Fingerprint Detection Using Canny Filter and DWT, a New Approach

  • Islam, Md. Imdadul;Begum, Nasima;Alam, Mahbubul;Amin, M.R.
    • Journal of Information Processing Systems
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    • v.6 no.4
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    • pp.511-520
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    • 2010
  • This paper proposes two new methods to detect the fingerprints of different persons based on one-dimensional and two-dimensional discrete wavelet transformations (DWTs). Recent literature shows that fingerprint detection based on DWT requires less memory space compared to pattern recognition and moment-based image recognition techniques. In this study four statistical parameters - cross correlation co-efficient, skewness, kurtosis and convolution of the approximate coefficient of one-dimensional DWTs are used to evaluate the two methods involving fingerprints of the same person and those of different persons. Within the contexts of all statistical parameters in detection of fingerprints, our second method shows better results than that of the first method.

Character Region Detection in Natural Image Using Edge and Connected Component by Morphological Reconstruction (에지 및 형태학적 재구성에 의한 연결요소를 이용한 자연영상의 문자영역 검출)

  • Gwon, Gyo-Hyeon;Park, Jong-Cheon;Jun, Byoung-Min
    • Journal of Korea Entertainment Industry Association
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    • v.5 no.1
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    • pp.127-133
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    • 2011
  • Characters in natural image are an important information with various context. Previous work of character region detection algorithms is not detect of character region in case of image complexity and the surrounding lighting, similar background to character, so this paper propose an method of character region detection in natural image using edge and connected component by morphological reconstructions. Firstly, we detect edge using Canny-edge detector and connected component with local min/max value by morphological reconstructed-operation in gray-scale image, and labeling each of detected connected component elements. lastly, detected candidate of text regions was merged for generation for one candidate text region, Final text region detected by checking the similarity and adjacency of neighbor of text candidate individual character. As the results of experiments, proposed algorithm improved the correctness of character regions detection using edge and connected components.