scholarly journals Ship infrared image edge detection based on an improved adaptive Canny algorithm

2018 ◽  
Vol 14 (3) ◽  
pp. 155014771876463 ◽  
Author(s):  
Lisang Liu ◽  
Fenqiang Liang ◽  
Jishi Zheng ◽  
Dongwei He ◽  
Jing Huang
Keyword(s):  
Edge Detection ◽  
Signal To Noise Ratio ◽  
Infrared Image ◽  
Histogram Equalization ◽  
Detection Algorithm ◽  
Equalization Algorithm ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Algorithm ◽  
Edge Detection Method

Influenced by light reflection and water fog interference, ship infrared images are mostly blurred and have low signal-to-noise ratio. In this paper, an improved adaptive Canny edge detection algorithm for infrared image of ship is proposed, which aims to solve the threshold of the traditional Canny cannot be adjusted automatically and the shortcomings of sensitivity to noise. The contrast limited adaptive histogram equalization algorithm is adopted to enhance the infrared image, the morphological filter replaces the Gauss filter to smooth the image, and the OTSU algorithm is utilized to adjust the high and low thresholds dynamically. The experimental results show that the improved Canny algorithm, which can not only improve the contrast of the image and automatically adjust the threshold but also reduce the background sea clutter and false edges, is an effective edge detection method.

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.

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.

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.

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 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.

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 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

scholarly journals 3D Image Edge Detection Algorithm for Depth Detection

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3555-3557
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
3 Dimensional ◽  
3D Objects ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
3D Scene ◽  
Edge Recognition

Showing a genuine 3 dimensional (3D) objects with the striking profundity data is dependably a troublesome and cost-devouring procedure. Speaking to 3D scene without a noise (raw image) is another case. With a honed technique for survey profundity measurement can be effortlessly gotten, without requiring any extraordinary instrument. In this paper, we have proposed an edge recognition process in a profundity picture dependent on the picture based smoothing and morphological activities.In this strategy, we have utilized the guideline of Median sifting, which has a prestigious element for edge safeguarding properties. The edge discovery was done dependent on the Canny Edge Detection Algorithm. Along these lines this strategy will help to identify edges powerfully from profundity pictures and add to advance applications top to bottom pictures

The Implementation of Infrared Image Edge Detection Algorithm Based on CNN on FPGA

2012 ◽  
Vol 41 (11) ◽  
pp. 1354-1358 ◽  
Author(s):  
王巍 WANG Wei ◽  
安友伟 AN You-wei ◽  
黄展 HUANG Zhan ◽  
丁锋 DING Feng ◽  
杨铿 YANG Keng ◽  
...  
Keyword(s):  
Edge Detection ◽  
Infrared Image ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Image Edge

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.

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