• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1540-1546
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• 2017

Digital image processing is widely used in various fields including the military, medical, image recognition system, robot and commercial sectors. But in the process of acquiring and transmitting digital images, noise is generated by various external causes. There are various types of general noise depending on the cause and form, but AWGN and impulse noise is one of the leading methods. Removing noise during image processing is essential to the pre-treatment process such as segmentation, image recognition and characteristic extraction. As such, this paper suggests an algorithm that distinguishes the non-edge area and edge area using the Canny edge to apply different filters to different areas in order to effectively remove noise from the image. To verify the effectiveness of the suggested algorithm, it was compared against existing methods using zoom images, edge images and PSNR(peak signal to noise ratio).

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.939-944
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• 2007

Edge is a significant element to represent boundary information between objects in images. There are various edge detection methods, which are based on differential operation, such as Sobel, Prewitt, Roberts, Canny, Laplacian, and etc. However the conventional methods have drawbacks as follow : (i) insensitivity to edges with gentle curve intensity, (ii) detection of double edges for edges with one pixel width. For the detection of edges, not only development of the effective operators but also that of appropriate thresholding methods are necessary. But it is very complicate problem to find an appropriate threshold. In this paper, we propose an edge detection method based on the region separateness between objects to overcome the drawbacks of the conventional methods, and a thresholding method for the proposed edge detection method. We show the effectiveness of the proposed method through experimental results obtained by applying the proposed and the conventional methods to well-known test images.

• 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 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2982-2988
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• 2014

The edge detection is a pre-processing of such as image segmentation, image recognition, etc, and many related studies are being conducted both in domestic and abroad. Representative edge detection methods are Sobel, Prewitt, Laplacian, Roberts and Canny edge detectors. Such existing methods are possible for superb detections of edges if edges are detected from videos without noises. However, for video degraded by the salt-and-pepper noise, the edge detection characteristic is shown to be insufficient due to the noise influence. Therefore, in this study, the area is separated as the top, down, left and right from the mask's center pixel first to acquire a superb edge detection characteristic from the video damaged by the salt-and-pepper noise. And the algorithm that detects the final edge by applying the directional mask on the assumed factor of mask that is obtained according to the result of determination for the noise status of representative pixel value of each area.

• 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.

• 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.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.139-142
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• 2006

본 연구는 장면 이미지로부터 텍스트에 존재하는 문자-에지 특징을 이용하여 텍스트를 추출하는 방법을 제안한다. 캐니(Canny)에지 연산자를 이용하여 장면 이미지로부터 에지를 추출하고, 추출된 에지로부터 16종류의 에지-맵 생성한다. 생성된 에지 맵을 재구성하여 문자 특징을 갖는 8종류의 문자-에지 맵을 만단다. 텍스트는 배경과 잘 분리되는 특징이 있으므로 텍스트에 존재하는 '문자-에지 맵'의 특징을 이용하여 텍스트를 추출한다. 텍스트 영역에 대한 검증은 문자-에지 맵의 분포와 텍스트에 존재하는 글자간의 공백 특징으로 한다. 제안한 방법은 다양한 종류의 장면 이미지를 실험대상으로 하였고, 텍스트는 적어도 2글자 이상으로 구성된다는 제한조건과 너무 크거나 작은 텍스트는 텍스트 추출에서 제외하였다. 실험결과 텍스트 영역 추출률은 약 83%를 얻었다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.235-239
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• 2002

운송 컨테이너의 식별자를 추출하고 인식하는 것은 컨테이너 식별자들의 크기나 위치가 정형화되어 있지 않고 외부의 잡음으로 인하여 식별자의 형태가 훼손되어 있기 때문에 어렵다 된 논문에서는 이러한 특성을 고려하여 컨테이너 영상에 대해 Canny 마스크를 이용하여 에지를 검출하고, 검출된 에지 정보를 이용하여 수직 블록과 수평 블록을 추출하여 컨테이너의 식별자 영역을 추출한다. 추출된 컨테이너의 식별자 영역에서 히스토그램 방법과 윤곽선 추적 알고리즘을 이용하여 개별 식별자를 추출한다. 컨테이너의 개별 식별자 인식은 ART1을 개선하여 지도 학습 방법과 결합한 개선된 신경망을 제안하여 적용한다. 실험 결과에서는 제안된 컨테이너 식별자 추출 린 인식 방법이 다양한 컨테이너 영상에 대해 효율적인 것을 보인다.