Subpixel Edge Detection for Segmentation of the Pulp Fiber Image

2014 ◽  
Vol 568-570 ◽  
pp. 696-700
Author(s):  
Hong Juan Shi ◽  
Kai Li Zhang ◽  
Qing Hua Li
Keyword(s):  
Edge Detection ◽  
Measurement Accuracy ◽  
Ccd Camera ◽  
Pulp Fiber ◽  
Pulp Fibers ◽  
Edge Point ◽  
Canny Operator ◽  
Improve Measurement ◽  
Measurement Results ◽  
Edge Detection Method

In this paper the problem of accurate edge detection for pulp fibers images is discussed. The images are acquired by the smart CCD camera. Subpixel edge detection is considered that applied in the system to improve the measurement accuracy of pulp fibers. The location of a precise edge is the basis of kink index, kink Angle, curl index and other measurement parameters for the pulp fibers. A new method for subpixel edge detection of the pulp fibers is introduced. Canny operator is used to get the pixel level edge. Each edge point determines five pixels in the gradient direction. Then the least squares fitting is used to locate its sub-pixel edge. The measurement results show that the proposed subpixel edge detection method is valid to improve measurement accuracy for real time measuring the pulp fiber parameters.

Application of Image Analysis Based on Canny Operator Edge Detection Algorithm in Measuring Railway Out-of-Gauge Goods

2014 ◽  
Vol 912-914 ◽  
pp. 1172-1176 ◽  
Author(s):  
Yong Han ◽  
Mu Qiao ◽  
Xue Wan ◽  
Qing Chang
Keyword(s):  
Edge Detection ◽  
Measurement Errors ◽  
Detection Algorithm ◽  
Digital Measurement ◽  
Contour Extraction ◽  
Mathematical Software ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Measurement Results ◽  
Transport Safety

In order to guarantee out-of-gauge freight transport safety, it is necessary to study digital measurement to improve measuring accuracy for out-of-gauge goods which is very difficult to master outline dimension. The process of edge detection and the algorithm of canny operator edge detection were introduced in this paper. Taking the transformer for example, contour extraction was carried out on the end and the widths of transverse and longitudinal height are measured through the mathematical software MATLAB. Finally, measurement results are validated based on the known data. The results showed that canny operator has high calculate precision, and the closer to the part calibrated with pixel calibration, smaller the measurement errors are.

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 Intelligent Point Cloud Edge Detection Method Based on Projection Transformation

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Juan Zhu ◽  
Xiaofeng Yue ◽  
Jipeng Huang ◽  
Zongwei Huang
Keyword(s):  
Edge Detection ◽  
Point Cloud ◽  
Detection Method ◽  
Target Point ◽  
Normal Vector ◽  
Edge Point ◽  
Vertical Projection ◽  
Cloud Data ◽  
Edge Detection Method ◽  
Projection Transformation

An edge detection method based on projection transformation is proposed. First, the vertical projection transformation is carried out on the target point cloud. Data X and data Y are normalized to the width and height of the image, respectively. Data Z is normalized to the range of 0-255, and the depth represents the gray level of the image. Then, the Canny algorithm is used to detect the edge of the projection transformed image, and the detected edge data is back projected to extract the edge point cloud in the point cloud. Evaluate the performance by calculating the normal vector of the edge point cloud. Compared with the normal vector of the whole data point cloud of the target, the normal vector of the edge point cloud can well express the characteristics of the target, and the calculation time is reduced to 10% of the original.

Improving the measurement accuracy of an absolute imaging position encoder via a new edge detection method

2017 ◽  
Vol 11 (4) ◽  
pp. 406-413 ◽  
Author(s):  
Nian Cai ◽  
Pan Xiao ◽  
Qian Ye ◽  
Han Wang ◽  
Xindu Chen ◽  
...  
Keyword(s):  
Edge Detection ◽  
Measurement Accuracy ◽  
Detection Method ◽  
Edge Detection Method

An Adaptive Edge Detection Method for Image Polluted by Hybrid Noise in Image Measurement

2011 ◽  
Vol 214 ◽  
pp. 156-162
Author(s):  
Bei Zhi Li ◽  
Hua Jiang Chen ◽  
Jian Guo Yang
Keyword(s):  
Edge Detection ◽  
Gaussian Noise ◽  
Impulse Noise ◽  
Detection Method ◽  
Selection Method ◽  
Threshold Selection ◽  
Hybrid Filter ◽  
Image Measurement ◽  
Canny Operator ◽  
Edge Detection Method

Edge detection directly affects the accuracy of image measurement. In this paper, focusing on the edge detection of the image of mechanical part polluted by hybrid noise consisting of Gaussian noise and impulse noise, an adaptive edge detection method is proposed. The proposed method combines a new hybrid filter smoothing noise adaptively with Canny operator to avoid the conflict of Canny operator between noise removing and edge locating, and uses Otsu threshold selection method to determine Dual-threshold of Canny operator adaptively. Using the gauge image polluted by hybrid noise as experiment object, the performance of the proposed method is evaluated qualitatively and quantitatively. Experimental results show that the proposed edge detection method has good performance.

Technical Note: Range verification system using edge detection method for a scintillator and a CCD camera system

2016 ◽  
Vol 43 (4) ◽  
pp. 1754-1759 ◽  
Author(s):  
Naoya Saotome ◽  
Takuji Furukawa ◽  
Yousuke Hara ◽  
Kota Mizushima ◽  
Ryohei Tansho ◽  
...  
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Ccd Camera ◽  
Technical Note ◽  
Camera System ◽  
Verification System ◽  
Edge Detection Method ◽  
Range Verification

scholarly journals Edge detection of foreign matter suspension image of high voltage transmission line based on improved Canny operator

2021 ◽  
Vol 2087 (1) ◽  
pp. 012091
Author(s):  
Yongjian Lin ◽  
Kanglin Liu ◽  
Baorong Wei ◽  
Yantai Wei ◽  
Kaiyuan Long
Keyword(s):  
Edge Detection ◽  
Transmission Line ◽  
High Voltage ◽  
Detection Rate ◽  
Foreign Matter ◽  
Canny Operator ◽  
High Voltage Transmission Line ◽  
Image Edge ◽  
High Voltage Transmission ◽  
Edge Detection Method

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.

An Adaptive Edge Detection Method Based on Canny Operator

2011 ◽  
Vol 255-260 ◽  
pp. 2037-2041
Author(s):  
Bai He Lang ◽  
Ling Yun Shen ◽  
Tai Lin Han ◽  
Yu Qun Chen
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Threshold Value ◽  
Detection Algorithm ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Sobel Operator ◽  
Otsu Method ◽  
Edge Detection Method ◽  
Roberts Operator

This paper proposes an adaptive Canny operator edge detection algorithm. The proposed method can automatically set the threshold value according to the different image gray-scale gradient histogram adaptively and improve the performance in the detail edge detection and good localization. Experiments show that this method produces better edge detection results performance than the Otsu method. Besides our method, Roberts operator, Prewitt operator, Sobel operator, Log operator and Canny operator based on Otsu algorithm are also tested for comparisons.

scholarly journals Adaptive Image Edge Extraction Based on Discrete Algorithm and Classical Canny Operator

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1749
Author(s):  
Phusit Kanchanatripop ◽  
Dafang Zhang
Keyword(s):  
Edge Detection ◽  
Feature Detection ◽  
Detection Method ◽  
Canny Operator ◽  
One Dimensional ◽  
Image Edge Detection ◽  
Discrete Algorithm ◽  
Detection Technology ◽  
Image Edge ◽  
Edge Detection Method

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.

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