• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.51-56
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• 2016

This paper proposes a new image enhancement method for an infrared thermal image. The proposed method uses both Laplacian and Prewitt edge detectors. Without a visible light, it uses an infrared image for the edge detection. The method subtracts contour images from the infrared thermal image. It results black contours of objects in the infrared thermal image. That makes the objects in the infrared thermal image distinguished clearly. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using various infrared thermal images. The results show that the proposed method is successful for image enhancement of an infrared thermal image.

• 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.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.78-89
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• 1992

In this paper, a multiresolution edge detction algorithm for speckle images is proposed. Due to the signal dependency of speckle images, the number of edge points detected depends on the local average intensity. Thus the edge detection method independent of the average intensity is required to detect properly real significant changes in an original signal. In the proposed method, candidate area is first selected based on the statistical propeties of speckle images,i.e., based on the busyness measure such as the CoV(coefficient of variation) and the difference between the real and theoretical CDF(cumulative density function). Then the real edges are extracted in a multiresolution environment. Computer simulation with test images shows that the proposed method reduces significantly false edges in relatively homogeneous areas while detects fine details properly.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1424-1433
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• 1995

The edge detection process serves to simplify the analysis of images by drastically reducing the amount of data to be processed, while preserving useful structural informations about object boundaries. At first, this paper proposes an edge detection algorithm to reduce the amount of computation. The gradients of pixels are calculated by using first order differential equations on the pixels with even rows and even columns or odd rows and odd columns, and they are compared with a threshold to decide edges. As a result, the computational complexity is reduced to one third or one forth compared with the provious ones. To enhance the accuracy of edge detection, a method with the adaptive threshold for each pixel window which is calculated by using characteristic values is proposed. In this case, the performance can be improved since the threshold is calculated properly for each window according to the local characteristics of corresponding window.

• The Journal of Bigdata
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• v.1 no.1
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• pp.19-22
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• 2016

Many Studies have been actively conducted on the early diagnosis of the crop pest utilizing IT technology. The purpose of the paper is to discuss on the image processing method capable of detecting the crop leaf pest prematurely by analyzing the image of the leaf received from the camera sensor. This paper proposes an algorithm of diagnosing leaf infection by utilizing an improved K means clustering method. Leaf infection grouping test showed that the proposed algorithm illustrated a better performance in the qualitative evaluation.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.1021-1024
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• 2000

In this paper we describe a nonparametric Wilcoxon test and a parametric Z 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[4] consider the range of possible values of test statistics for the threshold. From the experimental results of edge detection, the Z method performs sensitively to the noisy image, while the Wilcoxon method is robust over both noisy nd noise-free images. Comparison with our statistical tests and Sobel operator shows that our tests perform more effectively in both noisy and noise-free images.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2459-2461
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• 2003

본 논문은 차량 내에 설치된 두 대의 CCD 카메라를 이용하여 도로 영상으로부터 주행차선내에 있는 장애물을 인식하는 새로운 알고리즘을 제시한다. 제안된 알고리즘은 주행하는 차선과 관련이 있는 차선 정보만을 이용하여, 스테레오 영상에서 변이도를 추출할 수 있는 변이도 함수인 DLI(Disparity of lane-related information)를 정의하였다. DLI는 선행 차량과 같은 장애물은 주위보다 상대적으로 큰 에지값을 가진다는 특성을 이용하여, 주행차선 내에 있는 장애물의 유무를 검출하고 위치를 유추한다. 제안된 방법은 특징점의 탐색공간을 현저히 줄여 실시간 처리문제를 해결한 수 있는 장점을 가지고 있다. 본 논문에서는 DLI를 이용한 선행차량 인식기법의 성능을 검증하기 위하여 다양한 환경의 도로영상에 알고리즘을 적용하여 제안한 방법의 우수함을 확인하였다.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.294-296
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• 1996

The process of detecting edge in an image is an important component of many Pattern Recognition and Computer Vision applications. In many practical cases, there exist blurred images due to defocussing, movement of an object and so on. In addition, local perturbation noise can be added to the images. We propose the edge detection technique in blurred and noisy image. For this, we use Fuzzy pyramid linking mothod to remove noise and enhance the edge in images. We develop contrast intensifier using the concept of Fuzzy sets as a postprocessing.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.41-48
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• 2012

In this paper, we propose a method of edge detection for noisy image. The proposed method uses a progressive filter for noise reduction and a Sobel operator for edge detection. The progressive filter combines a median filter and a modified rational filter. The proposed method for noise reduction adjusts rational filter direction according to an edge in the image which is obtained by median filtering. Our method effectively attenuates the noise while preserving the image details. Edge detection is performed by a Sobel operator. This operator can be implemented by integer operation and is therefore relatively fast. Our proposed method not only preserves edge, but also reduces noise in uniform region. Thus, edge detection is well performed. Our proposed method could improve results using further developed Sobel operator. Experimental results show that our proposed method has better edge detection with correct positions than those by existing median and rational filtering methods for noisy image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.205-208
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• 2006

The position tracking of moving image for surveillance system is presented in this paper. The image of objects moving is detected with difference image between the background image not to be moved relatively and the forward moving image. The moving image is tracked with edge detection and moving vector to the object. The experiment result shows that the system enable to trail the position of moving objects obviously and is able to discriminate an infiltration.