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.

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.

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.

scholarly journals Research on Improved Canny Edge Detection Algorithm

2018 ◽  
Vol 232 ◽  
pp. 03053
Author(s):  
Ruiyuan Liu ◽  
Jian Mao
Keyword(s):  
Genetic Algorithm ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Noise Robustness ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Algorithm ◽  
Canny Edge Detection Algorithm

Aiming at the poor noise robustness of traditional Canny algorithm and the defect of false edge or edge loss, an edge detection algorithm using statistical algorithm for filtering denoising and using genetic algorithm to determine the optimal high and low threshold of image segmentation is proposed. Firstly, statistical filtering uses mean and variance to denoise, avoiding the problem of Gaussian denoising susceptible to interference in the traditional Canny algorithm, and ensuring the integrity of image edge information. Secondly, this article uses the genetic algorithm, design the crossover operator and genetic operator to modify the evolution of the population, and determine the optimal height threshold of the image edge connection to make the threshold more accurate. Finally, using MATLAB software to simulate, the results show that the improved Canny edge detection algorithm can further improve the anti-noise ability and robustness, and the edge location is more accurate.

Application of Improved Canny Algorithm on the IC Chip pin Inspection

2011 ◽  
Vol 317-319 ◽  
pp. 854-858
Author(s):  
Ying Huang ◽  
Qi Pan ◽  
Qi Liu ◽  
Xin Peng He ◽  
Yun Feng Liu ◽  
...  
Keyword(s):  
Edge Detection ◽  
Comprehensive Evaluation ◽  
Median Filter ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Algorithm ◽  
Improved Methods ◽  
Canny Edge Detection Algorithm

Machine vision is widely used in chip pin automation detection of defects, the accuracy of image edge extraction for detection result has very big effect. Canny edge detection algorithm is a kind of edge detection algorithm which have good comprehensive evaluation, but the Gaussian filter algorithm it used may cause image too smooth and fuzzy of the edge, and it is very sensitive for impulse noise. This paper discusses the improved methods of Canny, proposes an improved switch median filter algorithm, which is applied into Canny algorithm, makes the edge of IC Chip pin more complete and remove noise better.

scholarly journals Identification of Image Edge Using Quantum Canny Edge Detection Algorithm

2019 ◽  
Vol 13 (2) ◽  
pp. 133-144 ◽  
Author(s):  
Dini Sundani ◽  
◽  
Sigit Widiyanto ◽  
Yuli Karyanti ◽  
Dini Tri Wardani ◽  
...  
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Edge Detection Algorithm

Polynomial Interpolation Sub-Pixel Edge Detection Method Based on Improved Canny Operator

2014 ◽  
Vol 563 ◽  
pp. 203-207
Author(s):  
Kun Lin Yu ◽  
Zhi Yu Xie
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Polynomial Interpolation ◽  
Detection Algorithm ◽  
Edge Image ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Image Edge ◽  
Edge Detection Method

According to the shortcoming of traditional Canny edge detection algorithm is sensitive to noise and low positioning accuracy, this paper proposes an algorithm of Polynomial interpolation Sub-pixel edge detection based on improved Canny operator: We first use improved Canny operator edge detection algorithm to extract rough image edge, then use the quadratic Polynomial interpolation to calculate on the rough extraction edge, finally refine the edge image. Experiments show that the improved method is better than the traditional detection method can accurately locate the image edge.

A Novel Edge Detection Algorithm for Medical Image

2012 ◽  
Vol 151 ◽  
pp. 653-656
Author(s):  
Zhan Chun Ma ◽  
Xiao Mei Ning
Keyword(s):  
Edge Detection ◽  
Medical Image ◽  
Detection Algorithm ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Traditional Algorithm ◽  
Image Edge ◽  
Improved Algorithm

CANNY operator had widely usage for edge detection; however it also had certain deficiencies. So the traditional CANNY operator about this is improved and puts forward a kind of new algorithm used for image edge detection. Compared improved algorithm with traditional algorithm for edge detection, simulations shows that new algorithm is more effective for image edge detection and the clearer detection result is obtained.

scholarly journals Improved Canny Edge Detection Technique using S-Membership Function

2019 ◽  
Vol 8 (6) ◽  
pp. 43-49 ◽  
Keyword(s):  
Edge Detection ◽  
Membership Function ◽  
Detection Algorithm ◽  
Superior Performance ◽  
Threshold Values ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Canny Algorithm ◽  
Canny Edge Detection Algorithm

Traditional Canny edge detection algorithm is sensitive to noise, hence it may lose the weak edge information after noise removal and show poor adaptability of fixed parameters like threshold values. In view of these problems, this paper reports on the modification of canny edge detection algorithm using s-membership function. Adaptability of threshold values are achieved through S-membership function and is given as input to default Canny algorithm. The grayscale images have been analyzed for default Canny and modified Canny algorithm. To understand the performance of these algorithms it is essential to evaluate various statistical metrics. The proposed work states that the detailed statistical results and the images obtained reveal the superior performance of the modified Canny algorithm over the default Canny edge detection algorithm. Further the images obtained from modified Canny algorithm shows the marked edges with efficient image edge extraction and provide accurate information for image measurement.

scholarly journals Edge Location and Identification Method for Electronic Components based on Improved Canny Algorithm

2022 ◽  
Vol 16 ◽  
pp. 209-214
Author(s):  
Yuan Chao ◽  
Fan Shi ◽  
Wentao Shan ◽  
Dong Liang
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Identification Accuracy ◽  
Electronic Components ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Vision Inspection ◽  
Canny Edge ◽  
Canny Algorithm ◽  
Canny Edge Detection Algorithm

The position identification of SMD electronic components mainly uses Canny edge detection algorithm to detect the edges of specific elements, benefited from its computational simplicity. The traditional Canny algorithm lacks the adaptability in gradient calculation and double thresholds selection, which may affect the location and identification accuracy of specific elements in electronic components. In this paper, an improved canny edge detection algorithm is proposed. The gradient magnitude is calculated in four directions, i.e., horizontal, vertical, and diagonal. Both the high and low thresholds can be adaptively determined based on the grayscale distribution information, to increase the adaptability of edge identification. The experimental results show that the proposed method can better locate the true edges of specific elements in electronic components with a reasonable processing speed, compared with the traditional Canny algorithm, and has been successfully applied on practical real-time vision inspection on SMD electronic components.

scholarly journals Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Jianfang Cao ◽  
Lichao Chen ◽  
Min Wang ◽  
Yun Tian
Keyword(s):  
Edge Detection ◽  
Programming Model ◽  
Detection Algorithm ◽  
Detection Performance ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Parallel Programming Model ◽  
Hadoop Platform ◽  
Canny Edge ◽  
Canny Edge Detection Algorithm

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator’s dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

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