• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.133-141
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• 2005

An edge is where the intensity of an image moves from a low value to high value or vice versa. The edges tell where objects are. their shape and size. and something about their texture. Many traditional edge operators are derivative based and perform reasonably well for simple noise-free images. In recent, statistical edge detectors for complex images with noises have been described. This paper compares and analysis the performance of statistical edge detectors based on the T test and Wilcoxon test, and mathematical edge detectors based on Sobel operator, and the well-known Canny detector and Wavelet transformation detector, and provides the implementation of these edge detectors using Java on the web.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.337-340
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• 2000

조명 및 반사광의 성질에 의해 블러링이 발생하고 이런 영상을 인식하는 경우 정확한 에지 검출이 어렵게 된다. 이를 최적으로 검출하기 위해 일정하게 에지를 검출할 수 있는 가우시안 함수와 2차 미분 함수를 합성한 새로운 하이브리드 함수를 제안하고 실제 영상과 컨볼루션 한 후 함수의 $\sigma$값을 변화시키면서, Canny 알고리즘의 방향성 에지 검출 방법을 적용하여 에지를 검출하였다. 그 결과 Sobel, Robert, Canny 에지 검출방법보다 0.2~14㏈ 정도 안정적으로 에지가 검출되었다.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.33-40
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• 2009

Edge detection is very significant in low level image processing. However, majority edge detection methods are not only effective enough cause of the noise points' influence, even not flexible enough to different input images. In order to sort these problems, in this paper an algorithm is presented that has an extra noise reduction stage at first, and then automatically selects the both thresholds depending on gradient amplitude histogram and intra class minimum variance. Using this algorithm, can fade out almost all of the sensitive noise points, and calculate the propose thresholds for different images without setting up the practical parameters artificially, and then choose edge pixels by fuzzy algorithm. In finally, get the better result than the former Canny algorithm.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.107-108
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• 2016

Our study proposes the methods of distinguishing vehicle types using the interval and size of the car. The car videos converts the basic RGB model to Gray model for use and through Canny Edge Direction, it eliminates the background of the car while obtaining feature points through the detection of contours.

• 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.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.147-153
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• 2004

This paper proposes an efficient edge detection using Van der Waerden statistic in original and noisy images. An edge is where the intensity of an image moves from a low value to a high value or vice versa. We describe a nonparametric Wilcoxon test and a parametric T test based on statistical hypothesis testing for the detection of edges. We use the threshold determined by specifying significance level $\alpha$, while Bovik, Huang and Munson consider the range of possible values of test statistics for the threshold. From the experimental results of edge detection, the T and Wilcoxon method perform sensitively to the noisy image, while the proposed Waerden method is robust over both noisy and noise-free images under $\alpha$=0.0005. Comparison with our statistical test and Sobel, LoG, Canny operators shows that Waerden method perform more effectively in both noisy and noise-free images.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.359-371
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• 2011

Edge detection in images is an important step in image segmentation and object recognition as preprocessing for image processing. This paper presents a new edge detection using local histogram analysis based on wavelet transform. In this work, the wavelet transform uses three components (horizontal, vertical and diagonal) to find the magnitude of the gradient vector, instead of the conventional approach in which tw components are used. We compare the magnitude of the gradient vector with the threshold that is obtained from a local histogram analysis to conclude that an edge is present or not. Some experimental results for our edge detector with a Sobel, Canny, Scale Multiplication, and Mallat edge detectors on sample images are given and the performances of these edge detectors are compared in terms of quantitative and qualitative measures. Our detector performs better than the other wavelet-based detectors such as Scale Multiplication and Mallat detectors. Our edge detector also preserves a good performance even if the Sobel and Canny detector are sharply low when the images are highly corrupted.