• Title/Summary/Keyword: Sobel edge detection algorithm

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A Fine Dust Measurement Technique using K-means and Sobel-mask Edge Detection Method (K-means와 Sobel-mask 윤곽선 검출 기법을 이용한 미세먼지 측정 방법)

  • Lee, Won-Hyeung;Seo, Ju-Wan;Kim, Ki-Yeon;Lin, Chi-Ho
    • 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.

A Study on Edge Detection using Modified Histogram Equalization (변형된 히스토그램 평활화를 적용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • 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.

An Edge Detection Algorithm using Modified Mask in AWGN Environment (AWGN 환경에서 변형된 마스크를 이용한 에지 검출 알고리즘)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.892-894
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    • 2013
  • Edge has been utilized in various application fields with development of technique of digital image processing. In conventional edge detection methods, there are some methods using mask including Sobel, Prewitt, Roberts and Laplacian operator. Those methods are that implement is simple but generates errors of edge detection in images added AWGN(additive white Gaussian noise). Therefore, to compensate the defect of those methods, in this paper, an edge detection algorithm using modified mask is proposed, and it showed superior edge detection property in AWGN.

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A Study on Edge Detection Algorithm using Mask Shifting Deviation (마스크 이동 편차를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.8
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    • pp.1867-1873
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    • 2015
  • Edge detection is one of image processing techniques applied for a variety of purposes in a number of areas and it is used as a necessary pretreatment process in most applications. In the conventional edge detection methods, there are Sobel, Prewitt, Roberts and LoG, etc using a fixed weights mask. Since conventional edge detection methods apply the images to the fixed weights mask, the edge detection characteristics appear somewhat insufficient. Therefore in this study, an algorithm for detecting the edge is proposed by applying the cross mask based on the center pixel and up, down, left and right mask based on the surrounding pixels of center pixel in order to solve these problems. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.

A Study on Edge Detection using Gray-Level Transformation Function (그레이 레벨 변환 함수를 이용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.12
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    • pp.2975-2980
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    • 2015
  • Edge detection is one of image processing techniques applied for a variety of purposes in a number of areas and it is used as a necessary pretreatment process in most applications. Detect this edge has been conducted in various fields at domestic and international. In the conventional edge detection methods, there are Sobel, Prewitt, Roberts and LoG, etc using a fixed weights mask. Since conventional edge detection methods apply the images to the fixed weights mask, the edge detection characteristics appear somewhat insufficient. Therefore in this study, to complement this, preprocessing using gray-level transformation function and algorithm finding final edge using maximum and minimum value of estimated mask by local mask are proposed. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.

A Study on Mask-based Edge Detection Algorithm using Morphology (모폴로지를 이용한 마스크 기반 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.10
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    • pp.2441-2449
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    • 2015
  • In this digital information era, utilization of images are essential for various media, and the edge is an important characteristical information of an object in images that includes the size, location, direction and etc. Many domestic and international studies are being conducted in order to detect these edge. Existing edge detection methods include Sobel, Prewitt, Roberts, Laplacian, LoG and etc. which apply fixed weight value. As these existing edge detection methods apply fixed weight mask to the image, edge detection characteristic appears slightly insufficient. Accordingly, in order to supplement these problems, this study used bottom-hat transformation from mathematical morphology and opening operation in improving the image and proposed an algorithm that detects for the edge after calculating mask-based gradient. And to evaluate the performance of the proposed algorithm, a comparison was made against the existing Sobel, Roberts, Prewitt, Laplacian, LoG edge detection methods, in illustrating visual images, and similarities were compared by calculating the MSE value based on the standard of each image.

An Edge Detection Method using Modified Mask in Impulse Noise Environment (임펄스 잡음 환경에서 변형된 마스크를 이용한 에지 검출 방법)

  • Lee, Chang-Young;Kim, Nam-Ho
    • 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.

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A Study on Edge Detection using Weighted Value with Threshold (임계값에 따른 가중치를 이용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Hwang, Yeong-Yeun;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.886-888
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    • 2013
  • An edge includes information of objects such as magnitude, orientation, and location. Conventional edge detection methods to detect those edge are methods using Sobel, Prewitt, Roberts, Laplacian operator. Existing methods use fixed weighted mask to detect edges, and their edge detection characteristics are insufficient. Therefore, to remedy weakness of conventional methods, in this paper, an edge detection algorithm using weight with standard deviation and thresholds is proposed.

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A Study on Edge Detection Algorithm using Standard Deviation of Local Mask (국부 마스크의 표준편차를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.328-330
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    • 2015
  • Edge is a characteristic information that can easily obtain the size, direction and location of objects included in the image, and the edge detection is utilized as a preprocess processing in various image processing application sectors such as object detection and object recognition, etc. For the conventional edge detection methods, there are Sobel, Prewitt and Roberts. These existing edge detection methods are easy to implement but the edge detection characteristics are somewhat insufficient as fixed weighted mask is applied. Therefore, in order to compensate the problems of existing edge detection methods, in this paper, an edge detection algorithm was proposed after applying the weighted value according to the standard deviation and means within the local mask.

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FPGA-based Implementation of Fast Edge Detection using Sobel Operator (소벨 연산을 이용한 FPGA 기반 고속 윤곽선 검출 회로 구현)

  • Ryu, Sang-Moon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.8
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    • pp.1142-1147
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    • 2022
  • The edges of image should be detected first so that the objects in the image can be identified. An hardware-implemented edge detection algorithm outperforms its software version. Sobel operation is the most suitable algorithm for an hardware implementation of edge detection. And lots of works have been done to perform Sobel operations efficiently on FPGA-based hardware. This work proposes how to implement fast edge detection circuit on FPGA, which is based on the conventional circuit for edge detection using Sobel operator. The newly proposed circuit is suitable for processing images when the images are stored in memory devices and outperforms the conventional one with little additional FPGA resources. Both the conventional circuit and the proposed circuit were implemented on an FPGA. And the result showed that the proposed circuit almost doubles the performance in processing images and needs little additional FPGA resources.