• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.97-101
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• 2022

In this paper, we propose a method of measuring Fine dust in images using K-means and Sobel-mask based edge detection techniques using CCTV. The proposed algorithm collects images using a CCTV camera and designates an image range through a region of interest. When clustering is completed by applying the K-means algorithm, outline is detected through Sobel-mask, edge strength is measured, and the concentration of fine dust is determined based on the measured data. The proposed method extracts the contour of the mountain range using the characteristics of Sobel-mask, which has an advantage in diagonal measurement, and shows the difference in detection according to the concentration of fine dust as an experimental result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1221-1227
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• 2015

Edge detection is one of the important technologies to simplify images in the text, lane and object recognition implementation process, and various studies are actively carried out at home and abroad. Existing edge detection methods include a method to detect edge by applying directional gradient masks in spatial space, and a mathematical morphology-based edge detection method. These existing detection methods show insufficient edge detection results in excessively dark or bright images. In this regard, to complement these drawbacks, we proposed an algorithm using the Sobel and histogram equalization among the existing methods.

• Journal of IKEEE
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• v.19 no.1
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• pp.10-17
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• 2015

In this Paper, an efficient method of FPGA based design and implementation of Sobel Edge detector block using 3-Line buffers is presented. The FPGA provides the proper and sufficient hardware for image processing algorithms with flexibility to support Sobel edge detection algorithm. A pipe-lined method is used to implement the edge detector. The proposed Sobel edge detection operator is an model using of Finite State Machine(FSM) which executes a matrix mask operation to determine the level of edge intensity through different of pixels on an image. This approach is useful to improve the system performance by taking advantage of efficient look up tables, flip-flop resources on target device. The proposed Sobel detector using 3-line buffers is synthesized with Xilinx ISE 14.2 and implemented on Virtex II xc2vp-30-7-FF896 FPGA device. Using matlab, we show better PSNR performance of proposed design in terms of 3-Line buffers utilization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.787-789
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• 2017

Edge detection is used in many applications such as image analysis, pattern recognition and computer vision. Existing edge detection methods, there is such Sobel, Prewitt, Roberts, and LoG(Laplacian of Gaussian). In the conventional edge detection method, edge detection is insufficient because the change of the pixel brightness is small when the original image is in low illumination. Therefore, in this paper, we proposed a function to convert the pixel brightness of low illumination image to solve this problem. And it was compared by applying the conventional methods Sobel, Prewitt, Roberts, LoG(Laplacian of Gaussian) to determine the performance of the pixel brightness transform function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.672-674
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• 2011

Edge contains important information to analyze the characteristics of the images. Edge detection has been a lot utilized in areas such as computer vision and image processing etc.. And sobel, prewitt, roberts are representative methods among the initially used methods. Although these conventional methods easily detect large change points of slope of brightness, optional directional edge detection abilities of conventional edge detection are not efficient. Therefore, in this paper, to complement the shortcomings of existing edge detection method, we proposed adaptive edge detection method considering direction information. through simulatioopn, we verify abilities of our method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.801-803
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• 2014

In the modern society, image processing is utilized in various fields. Edge detection used for image processing as such is essential for most of the applications. Accordingly, there are studies conducted both in and out of Korea in order to detect edge. Representative edge detection methods include Sobel, Prewitt and Roberts. However, these methods are rather limited when it comes to the edge detection characteristics when used for the image with damaged AWGN(additive white Gaussian noise). Thus, this paper presented edge detection method utilizing local mask in order to overcome the shortcomings of the existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.404-406
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• 2013

An image edge has been utilized as preprocessing procedure in various field such as object detection, object recognition. there are Sobel, Prewitt, Roberts, Laplacian as conventional edge detection methods. existing methods are implement is simple, but edge detection characteristics is insufficient in impulse noise area. Therefore, to compensate the defect of conventional methods, in this paper, an edge detection algorithm using modified mask is proposed.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.207-212
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• 2015

We propose a noise estimation method using edge detection in moving pictures. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use Sobel and morphological closing operators which are robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of moving images and has better results than those of existing noise estimation methods. Also, proposed algorithm can be efficiently applied to image and video applications.

• Journal of Astronomy and Space Sciences
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• v.33 no.4
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• pp.313-318
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• 2016

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.