scholarly journals Grey Relevancy Degree and Improved Eight-Direction Sobel Operator Edge Detection

2021 ◽  
Vol 12 (02) ◽  
pp. 43-55
Author(s):  
Yang Yang ◽  
Lianxin Wei
Keyword(s):  
Edge Detection ◽  
Sobel Operator

Design of an image edge detection filter using the Sobel operator

10.1109/4.996 ◽  
1988 ◽  
Vol 23 (2) ◽  
pp. 358-367 ◽  
Author(s):  
N. Kanopoulos ◽  
N. Vasanthavada ◽  
R.L. Baker
Keyword(s):  
Edge Detection ◽  
Sobel Operator ◽  
Image Edge Detection ◽  
Image Edge ◽  
Detection Filter

scholarly journals A Proposed Approach to Determine the Edges in SAR images

2020 ◽  
pp. 185-192
Author(s):  
Rabab Farhan Abbas
Keyword(s):  
Edge Detection ◽  
Electromagnetic Waves ◽  
Operator Method ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Edge Image ◽  
Sar Images ◽  
Wavelet Method ◽  
Radar Images ◽  
Sobel Operator

Radar is the most eminent device in the prolonged scattering era The mechanisms involve using electromagnetic waves to take Synthetic Aperture Radar (SAR) images for long reaching. The process of setting edges is one of the important processes used in many fields, including radar images, which assists in showing objects such as mobile vehicles, ships, aircraft, and meteorological and terrain forms. In order to accurately identify these objects, their edges must be detected. Many old-style methods are used to isolate the edges but they do not give good results in the  determination process. Conservative methods use an operator to detect the edges, such as the Sobel operator which is used to perform edge detection where the edge does not appear well.      The proposed method which combines Ridgelet transform, Bezier curve and Sobel operator is used to detect edges very efficiently. Ridghelet transform resolves the harms in the wavelet transform and it can well detect the edges in images. Bezier curve can profit gradual variation of the data and their mutability. Hence, the efficiency of the edged image is improved and, when used with Sobel operator, the quality of the edge image become very good. The data show that the advocated method has superior fallouts over the Sobel edge detection and the wavelet method in both subjective and impartial experiments. While the Peak Signal to Noise Ratio(PSNR) values were equal to 9.3812, 9.8918, 9.6521 and 9.0743using the Sobel operator method and to10.2564, 10.7927, 10.5612and 10.8633 using the wavelet method, they were increased in the proposed method to 12.6542, 12.9514, 12.8574 and 12.3013 respectively.

scholarly journals Feature Extraction of Gear Fault Signal Based on Sobel Operator and WHT

2013 ◽  
Vol 20 (3) ◽  
pp. 551-559 ◽  
Author(s):  
Jian-Hua Cai ◽  
Wei-Wen Hu
Keyword(s):  
Feature Extraction ◽  
Edge Detection ◽  
Hough Transform ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Cross Term ◽  
Time Performance ◽  
Sobel Operator ◽  
Gear Fault ◽  
Influence Of Noise

Taking Wigner-Ville distribution of gear fault signal as a picture,Sobeloperator was applied for edge detection of picture and then Hough transform was used to extract signal feature. Some simulated and measured signals have been processed to demonstrate the effectiveness of new method, which was compared with traditional Wigner-Hough transform and SPWD-Hough transform. The results show that the proposed method can suppress cross term which is produced from using Wigner-Ville distribution to analyze multi-component signal, especially under the condition of low signal to noise ratio. The improved Wigner-Hough transform can effectively suppress the influence of noise and has a good real-time performance because its algorithm is fast. The proposed method provides an effective method to determine the state of gear accurately.

Edge Detection Based on a Fuzzy Inference System

2011 ◽  
Vol 121-126 ◽  
pp. 4436-4440
Author(s):  
Shu Liang Sun ◽  
Cheng Lian Liu ◽  
Si Sheng Chen
Keyword(s):  
Edge Detection ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Linear Filter ◽  
High Contrast ◽  
Contrast Variation ◽  
Good Effort ◽  
Inference System ◽  
First Order ◽  
Sobel Operator

First-order linear filter is a wide application algorithm to detect edge in digital image. However it dosen’t make good effort to the image where contrast varies much, or luminance takes on non-uniform. In this paper, a fuzzy inference system (FIS) is made up and used to detect edges. The experiment shows that FIS is much better in edge detection when the image with high contrast variation than with the linear Sobel operator. The FIS is also more precise in edge detection than Sobel operator.

Application of Image Processing in Plasma Jet Morphological Analysis

2012 ◽  
Vol 229-231 ◽  
pp. 1136-1139 ◽  
Author(s):  
Xiao Jing Tian ◽  
Hua Jun Dong ◽  
Da Peng Yin ◽  
Zi Yu Zhao
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Morphological Analysis ◽  
Detection Method ◽  
Plasma Jet ◽  
Improved Method ◽  
Forming Quality ◽  
Sobel Operator ◽  
Image Morphology ◽  
Edge Detection Method

The morphology of plasma jet (PJ) directly demonstrates whether the procedure of spray processes is stable. The paper proposes an acquisition system of PJ images and an improved edge detection method is presented to get the morphology of PJ. Firstly, the PJ images are gray enhanced to remove the influence of noises. Then they are enhanced with edge sharpening. At last, they are edge detected through Canny, Laplacian and Sobel operator. From the results we can see that the improved method can get more clear and more complete PJ image morphology than traditional one. The processing methods provide foundation for the online detection of PJ morphology and for diagnosing the forming quality.

A novel real-time resource efficient implementation of Sobel operator-based edge detection on FPGA

2014 ◽  
Vol 101 (12) ◽  
pp. 1705-1715 ◽  
Author(s):  
Sanjay Singh ◽  
Anil K Saini ◽  
Ravi Saini ◽  
A.S. Mandal ◽  
Chandra Shekhar ◽  
...  
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Efficient Implementation ◽  
Sobel Operator ◽  
Time Resource

scholarly journals Comparative Analysis of Image Quality Values on Edge Detection Methods

2020 ◽  
Vol 4 (2) ◽  
pp. 345-351
Author(s):  
Wicaksono Yuli Sulistyo ◽  
Imam Riadi ◽  
Anton Yudhana
Keyword(s):  
Image Processing ◽  
Comparative Analysis ◽  
Edge Detection ◽  
Computer Technology ◽  
Detection Method ◽  
Detection Methods ◽  
Sobel Operator ◽  
Image Edge Detection ◽  
Image Edge ◽  
Edge Detection Method

Identification of object boundaries in a digital image is developing rapidly in line with advances in computer technology for image processing. Edge detection becomes important because humans in recognizing the object of an image will pay attention to the edges contained in the image. Edge detection of an image is done because the edge of the object in the image contains very important information, the information obtained can be either size or shape. The edge detection method used in this study is Sobel operator, Prewitt operator, Laplace operator, Laplacian of Gaussian (LoG) operator and Kirsch operator which are compared and analyzed in the five methods. The results of the comparison show that the clear margins are the Sobel, Prewitt and Kirsch operators, with PSNR calculations that produce values ​​above 30 dB. Laplace and LoG operators only have an average PSNR value below 30 dB. Other quality comparisons use the histogram value and the contrast value with the highest value results in the Laplace and LoG operators with an average histogram value of 110 and a contrast value of 24. The lowest histogram and contrast value are owned by the Sobel and Prewitt operators.  

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