scholarly journals IMPROVEMENT OF FABRIC DETECTION ALGORITHM BASED ON SOBEL OPERATOR

2020 ◽  
pp. 55-56
Author(s):  
Zhang Chao ◽  
Yang Lianhe
Keyword(s):  
Detection Algorithm ◽  
Adaptive Threshold ◽  
Threshold Selection ◽  
Sobel Operator ◽  
Judgment Error ◽  
Selection Threshold ◽  
Gradient Calculation ◽  
Edge Points ◽  
Image Edge ◽  
Influence Of Noise

The traditional Sobel operator has incomplete edge detection, and improper selection threshold causes edge judgment error. In this paper, non-maximum suppression combined with adaptive threshold selection is proposed for fabric defect detection. This method uses bilateral filtering for image preprocessing to eliminate the influence of noise and illumination imbalance on the image. Increase by 45 per cent。and 135。gradient calculation in two directions, using non-maximum suppression algorithm to refine the image edge, and reduce the misjudgment of edge points by adaptive threshold selection.

A WT-Based Edge Detection with Adaptive Threshold

2011 ◽  
Vol 204-210 ◽  
pp. 1386-1389
Author(s):  
Deng Yin Zhang ◽  
Li Xiao ◽  
Shun Rong Bo
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Threshold Value ◽  
Detection Algorithm ◽  
Adaptive Threshold ◽  
Value Iteration ◽  
Edge Detection Algorithm ◽  
Detection Algorithms ◽  
Image Edge ◽  
Threshold Setting

The existing edge detection algorithms with wavelet transform need to artificially set the threshold value and are lack of flexibility.To salve the limitations, in this paper, we propose a WT(wavelet transform)-based edge detection algorithm with adaptive threshold, which uses threshold value iteration method to achieve adaptive threshold setting. Comparison of experiment results for the CT image shows that the method which improve the clarity and continuity of the image edge can effectively distinguish edge and noise, and get more completely information of the edge. It has good application value in the fields of medical clinical diagnosis and image processing.

scholarly journals Edge Detection of Agricultural Products Based on Morphologically Improved Canny Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaokang Yu ◽  
Zhiwen Wang ◽  
Yuhang Wang ◽  
Canlong Zhang
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Agricultural Products ◽  
Canny Operator ◽  
Traditional Algorithm ◽  
Edge Points ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Algorithm ◽  
Canny Edge Detection Algorithm

The traditional canny edge detection algorithm has its limitations in the aspect of antinoise interference, and it is susceptible to factors such as light. To solve these defects, the Canny algorithm based on morphological improvement was proposed and applied to the detection of agricultural products. First, the algorithm uses the open and close operation of morphology to form a morphological filter instead of the Gaussian filter, which can remove the image noise and strengthen the protection of image edge. Second, the traditional Canny operator is improved to increase the horizontal and vertical templates to 45° and 135° to improve the edge positioning of the image. Finally, the adaptive threshold segmentation method is used for rough segmentation, and on this basis, double detection thresholds are used for further segmentation to obtain the final edge points. The experimental results show that compared with the traditional algorithm applied to the edge detection of agricultural products, this algorithm can effectively avoid the false contour caused by illumination and other factors and effectively improve the antinoise interference while more accurate and fine detection of the edge of real agricultural products.

scholarly journals Research on edge detection algorithm based on improved sobel operator

2020 ◽  
Vol 309 ◽  
pp. 03031
Author(s):  
Lili Han ◽  
Yimin Tian ◽  
Qianhui Qi
Keyword(s):  
Edge Detection ◽  
Mathematical Morphology ◽  
Detection Algorithm ◽  
Noise Sensitivity ◽  
Edge Detection Algorithm ◽  
Sobel Operator ◽  
Edge Location ◽  
Image Edge ◽  
Sobel Edge Detection ◽  
Suppress Noise

In order to solve the shortcomings of traditional Sobel edge detection operator, such as low accuracy of image edge location and rough edge extracted, an improved edge detection algorithm based on Sobel operator is proposed. Firstly, in the aspect of the accuracy of edge detection, the direction template is increased from two directions of horizontal and vertical to eight directions; secondly, in terms of the rough edge extracted and the noise sensitivity, combined with the operation of mathematical morphology, the edge can be refined, and at the same time, some part of the noise can be suppressed. The experiment results show that the improved edge detection algorithm has a better accuracy in image positioning, and a certain ability to suppress noise. Finally, the detected image edge of the image is more delicate and clear than the traditional Sobel operator.

Adaptive Harris corner detection algorithm based on iterative threshold

2017 ◽  
Vol 31 (15) ◽  
pp. 1750181 ◽  
Author(s):  
Zhicheng Wang ◽  
Rong Li ◽  
Zhihao Shao ◽  
Mengxin Ma ◽  
Jianhui Liang ◽  
...  
Keyword(s):  
Threshold Value ◽  
Detection Algorithm ◽  
Adaptive Threshold ◽  
Corner Detection ◽  
Threshold Selection ◽  
Harris Corner ◽  
Simulation Results ◽  
Threshold Setting ◽  
Harris Corner Detection ◽  
Iterative Threshold

An adaptive Harris corner detection algorithm based on the iterative threshold is proposed for the problem that the corner detection algorithm must be given a proper threshold when the corner detection algorithm is extracted. In order to avoid the phenomenon of clustering and restrain the pseudo corner, this algorithm realizes the adaptive threshold selection by iteration instead of the threshold value of the Harris corner detection algorithm. Simulation results show that the proposed method achieves good results in terms of threshold setting and feature extraction.

scholarly journals An Intelligent Nonparametric GS Detection Algorithm Based on Adaptive Threshold Selection

2013 ◽  
Vol 1 (4) ◽  
pp. 387-392
Author(s):  
Lin Zhang ◽  
Zhi-jian Zhao ◽  
Jian Guan ◽  
You He
Keyword(s):  
Detection Algorithm ◽  
Adaptive Threshold ◽  
Threshold Selection

An Effective Image Edge Detection Algorithm – Fuzzy Box-Counting

2014 ◽  
Vol 543-547 ◽  
pp. 2711-2715
Author(s):  
Li Ma ◽  
Li Shang ◽  
Long Zhang ◽  
Wei Shi Shao
Keyword(s):  
Edge Detection ◽  
Fuzzy Theory ◽  
Detection Algorithm ◽  
Detection Methods ◽  
Box Counting ◽  
Image Edge Detection ◽  
Box Counting Dimension ◽  
Edge Points ◽  
Image Edge

Edge detection plays an important role in computer vision and image processing. Fractal and Fuzzy theory show significant effect in the edge detection and have attracted much attention. Compared with traditional edge detection methods, this paper proposes a Fuzzy Box-counting Dimension Method (FBDM). This algorithm introduces the pre-judging mechanism to improve the speed of image segmentation, and the self-adaptive dimension threshold and the voting mechanism under multi-windows to improve the accuracy of the determination of edge points. Finally, closest principle is used to clear edge and reduce noise. Experimental results show FBDM can improve the precision of image edge detection effectively without pretreatment, and it has a very superior de-noising performance.

Application of Improved Canny Edge Detection Algorithm in Coal-Rock Interface Recognition

2012 ◽  
Vol 220-223 ◽  
pp. 1279-1283 ◽  
Author(s):  
Li Hong Dong ◽  
Peng Bing Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Rock Interface ◽  
Coal Rock ◽  
Image Edge ◽  
Canny Algorithm ◽  
Canny Edge Detection Algorithm

The coal-rock interface recognition is one of the critical automated technologies in the fully mechanized mining face. The poor working conditions underground result in the seriously polluted edge information of the coal-rock interface, which affects the positioning precision of the shearer drum. The Gaussian filter parameters and the high-low thresholds are difficult to select in the traditional Canny algorithm, which causes the information loss of gradual edge and the phenomenon of false edge. Consequently, this paper presents an improved Canny edge detection algorithm, which adopts the adaptive median filtering algorithm to calculate the thresholds of Canny algorithm according to the grayscale mean and variance mean. This algorithm can protect the image edge details better and can restrain the blurred image edge. Experimental results show that this algorithm has improved the edge extraction effect under the case of noise interference and improved the detection precision and accuracy of the coal-rock image effectively.

Surface Image Edge Detection Algorithm Based on Grey Relational Analysis

2012 ◽  
Vol 461 ◽  
pp. 343-346 ◽  
Author(s):  
Gang Li ◽  
Ying Fang ◽  
Ya La Tong
Keyword(s):  
Edge Detection ◽  
Good Method ◽  
Detection Algorithm ◽  
Relational Model ◽  
Small Data ◽  
The Road ◽  
Image Edge Detection ◽  
Surface Image ◽  
Image Edge ◽  
Grey Relational

Automatic detection of pavement cracks is one of the very hot topics. For the characteristics of “small data, poor information” in the surface image processing, we construct ed a grey image relational model to characterize the local image edge feature, by selecting the appropriate threshold to extract the edge of appropriate level. Finally, simulation experiments show that the new algorithm can effectively improve the road edge detection results, and it is an effective good method worthy further study.

An Improved Edge Detection Algorithm Based on Canny Operator

2013 ◽  
Vol 347-350 ◽  
pp. 3541-3545 ◽  
Author(s):  
Dan Dan Zhang ◽  
Shuang Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Image Simulation ◽  
Edge Image ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Edge Detection Algorithm

The traditional Canny edge detection algorithm is analyzed in this paper. To overcome the difficulty of threshold selecting in Canny algorithm, an improved method based on Otsu algorithm and mathematical morphology is proposed to choose the threshold adaptively and simultaneously. This method applies the improved Canny operator and the image morphology separately to image edge detection, and then performs image fusion of the two results using the wavelet fusion technology to obtain the final edge-image. Simulation results show that the proposed algorithm has better anti-noise ability and effectively enhances the accuracy of image edge detection.

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