scholarly journals Research on Subpixel Algorithm of Fixed-Point Tool Path Measurement

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xi Zhang ◽  
Zixie Guo ◽  
Xiangwei Liu ◽  
Longjia Zhang

Tool safety is an important part of machining and machine tool safety, and machine tool path image detection can effectively obtain the in-machine condition of a tool. To obtain an accurate image edge and improve image processing accuracy, a novel subpixel edge detection method is proposed in this study. The precontour is segmented by binarization, the second derivative in the neighborhood of the demand point is calculated, and the obtained value is sampled according to the specified rules for curve fitting. The point whose curve ordinate is 0 is the subpixel position. The experiment proves that an improved subpixel edge can be obtained. Results show that the proposed method can extract a satisfactory subpixel contour, which is more accurate and reliable than the edge results obtained by several current pixel-level operators, such as the Canny operator, and can be used in edge detection with high-accuracy requirements, such as the contour detection of online tools.

2014 ◽  
Vol 563 ◽  
pp. 203-207
Author(s):  
Kun Lin Yu ◽  
Zhi Yu Xie

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.


2021 ◽  
Vol 2087 (1) ◽  
pp. 012091
Author(s):  
Yongjian Lin ◽  
Kanglin Liu ◽  
Baorong Wei ◽  
Yantai Wei ◽  
Kaiyuan Long

Abstract In the edge detection of foreign object hanging image of high voltage transmission line, it is easy to appear that multiple responses will appear at one image edge point, which affects the detection effect. Based on the improved Canny operator, an edge detection method for foreign matter suspension image of high voltage transmission line is designed. The collected image is preprocessed in three steps: gray processing, optical correction and noise reduction, so as to better reflect the characteristics of the original image and improve the image quality. The non-uniform distribution of potential energy of foreign body hanging image data field is used to locate the image area of foreign body hanging. The morphological filter can extract the local noise and make the image clearer. The Canny operator is improved to obtain the partial derivative of the distance measurement function and automatically update the threshold to eliminate the multi-level response. The test results show that the method in this paper is better than the image edge detection method based on Canny operator and Sobel operator in three indexes: positive detection rate, false detection rate and missed detection rate.


Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1749
Author(s):  
Phusit Kanchanatripop ◽  
Dafang Zhang

In order to improve the accuracy of image edge detection, this paper studies the adaptive image edge detection technology based on discrete algorithm and classical Canny operator. First, the traditional sub-pixel edge detection method is illustrated based on the related literature research. Then, Canny operator is used for detection, the edge model of the quadric curve is established using discrete data, and the adaptive image edge parameters are obtained using one-dimensional gray moment. Experimental results show that the accuracy of feature detection is 99%, which can be applied to the practice of image edge detection to a certain extent.


2014 ◽  
Vol 539 ◽  
pp. 141-145
Author(s):  
Shui Li Zhang

This paper presents new theorems Stevens edge detection method based on cognitive psychology on. Firstly, based on the number of the image is decomposed into high-frequency and low-frequency information, and the high-frequency information extracted by subtracting the maximum number of images to the image after the filter, then the amount of high frequency information into psychological cognitive psychology based on Stevenss theorem. The algorithm suppression refined edge after the non-minimum, applications Pillar K-means algorithm to extract image edge. Experimental results show that: the brightness of the image is converted to the amount of psychological edge can better unify under different brightness values.


2013 ◽  
Vol 347-350 ◽  
pp. 3541-3545 ◽  
Author(s):  
Dan Dan Zhang ◽  
Shuang Zhao

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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