The Study of an Improved Fuzzy Edge Detection Algorithm in the Radial Tire Quality Detection

2011 ◽  
Vol 317-319 ◽  
pp. 968-971 ◽  
Author(s):  
Fang Yuan Li
Keyword(s):  
Service Life ◽  
Detection Method ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Radial Tire ◽  
Fuzzy Algorithm ◽  
X Ray ◽  
Inverse Transform ◽  
Quality Detection ◽  
Improved Algorithm

The internal radial tire defects will affect the performance and the service life of the automobile. But the traditional detection method is to observe and detect in eyes using X-ray map which result that a lot of quality problems can not properly been judged out. This paper describes the X-ray image recognition using a fuzzy algorithm. The improved algorithm simplifies the traditional fuzzy algorithm complexity without the transform and inverse transform. The experimental results show that the improved algorithm makes the computational efficiency and extract more refined and clear edge for the radial tire which can correctly identify the failure and provide the necessary data processing.

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.

The Research on Application of New Technique in Road Quality Detection

2014 ◽  
Vol 685 ◽  
pp. 413-416
Author(s):  
Yan Xiao
Keyword(s):  
Service Life ◽  
Detection Method ◽  
Main Principle ◽  
Transient Vibration ◽  
Highway Engineering ◽  
Quality Detection ◽  
Operation Techniques ◽  
Ring Method ◽  
Research On Application ◽  
Non Destructive

In order to be able to maintain the safety ,stabilize the operation, and prolong the service life of highway engineering, it is necessary to place particular emphasis on the detection of highway engineering. In view of the current imperfection existed in operation techniques of cutting-ring method and sand replacement method.This paper puts forward to a kind of non-destructive detection method for highway engineering based on transient vibration signals.The author makes a detailed analysis and discussion on the main principle and application of the detection method.

Improved Algorithm for Sub-Pixel Edge Detection Based on Zernike Moments

2011 ◽  
Vol 341-342 ◽  
pp. 763-767
Author(s):  
Bao Yong Zhao ◽  
Ying Jian Qi
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Zernike Moments ◽  
The Other ◽  
Original Image ◽  
Edge Detection Algorithm ◽  
Series Of Experiments ◽  
The One ◽  
New Criterion ◽  
Improved Algorithm

The principle of Zernike moments and the method of sub-pixel edge detection based on Zernike moments were introduced in this paper. With the consideration of the limitation of the sub-pixel edge detection algorithm by Ghosal, such as the lower location precision of the edge and the extracted wider edge than that of the original image, an improved algorithm was proposed. On the one hand, a mask of size nine multiply nine was calculated and could be applied for the edge detection. On the other hand, a new criterion for edge detection was put forward. Additionally, a series of experiments were designed and implemented. The experiment results show that accuracy of the improved algorithm is higher than that obtained from using other size templates and Ghosal algorithm.

scholarly journals A Novel Edge Detection Method Based on the Regularized Laplacian Operation

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 697
Author(s):  
Huilin Xu ◽  
Yuhui Xiao
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Regularization Parameter ◽  
Image Data ◽  
Detection Algorithm ◽  
Edge Detector ◽  
Rotation Symmetry ◽  
Edge Detection Algorithm ◽  
Choice Strategy ◽  
Edge Detection Method

In this paper, an edge detection method based on the regularized Laplacian operation is given. The Laplacian operation has been used extensively as a second-order edge detector due to its variable separability and rotation symmetry. Since the image data might contain some noises inevitably, regularization methods should be introduced to overcome the instability of Laplacian operation. By rewriting the Laplacian operation as an integral equation of the first kind, a regularization based on partial differential equation (PDE) can be used to compute the Laplacian operation approximately. We first propose a novel edge detection algorithm based on the regularized Laplacian operation. Considering the importance of the regularization parameter, an unsupervised choice strategy of the regularization parameter is introduced subsequently. Finally, the validity of the proposed edge detection algorithm is shown by some comparison experiments.

scholarly journals Automated segmentation of knee thermal imaging and X-ray in evaluation of rheumatoid arthritis

2018 ◽  
Vol 7 (2.8) ◽  
pp. 326 ◽  
Author(s):  
U Snekhalatha ◽  
T Rajalakshmi ◽  
M Gobikrishnan
Keyword(s):  
Rheumatoid Arthritis ◽  
Thermal Imaging ◽  
Detection Algorithm ◽  
Thermal Image ◽  
Automated Segmentation ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
X Ray ◽  
Canny Edge ◽  
Canny Edge Detection Algorithm

Rheumatoid arthritis (RA) is a long lasting autoimmune disorder that affects the multiple joints of human body. The aim and objective of the study was i) to implement the automated segmentation of knee x-ray image and thermal image using fuzzy c means  and canny edge detection algorithm. ii) To compare both the imaging modalities by means of feature extraction and correlate with the biochemical method as standard. Fifteen subjects with RA in knee region and 15 healthy controls were included in this study. The segmentation of thermal images was performed using fuzzy c-means algorithm and x-ray segmentation was implemented using canny edge detection algorithm. The skin surface temperature weremeasured in the thermal image of knee regionin both RA and control subjects. The features wereextracted from the segmented region of the knee x-ray image. The automated segmentation implemented in thermal imaging provided better results compared to x-ray image segmentation process. The thermal imaging feature and x-ray imaging features correlated significantly with the standard parameters.

An Effective Method for Defects Detection in Radiographic Images of Welds Based on Edge Detection and Morphology

2013 ◽  
Vol 290 ◽  
pp. 71-77
Author(s):  
Wen Ming Guo ◽  
Yan Qin Chen
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Detection Algorithm ◽  
Morphological Processing ◽  
Radiographic Images ◽  
X Ray ◽  
Weld Defects ◽  
Detection Algorithms ◽  
Detection Quality

In the current industrial production, as steel weld X-ray images are low contrasted and noisy, the efficiency and precision can’t be both ensured. This paper has studied three different edge detection algorithms and found the most suitable one to detect weld defects. Combined with this edge detection algorithm, we proposed a new weld defects detection method. This method uses defect features to find the defects in edge images with morphological processing. Compared to the traditional methods, the method has ensured detection quality of weld defects detection.

scholarly journals Application of an edge detection algorithm for surface determination in industrial X-ray computed tomography

2022 ◽  
Author(s):  
Matthias Busch ◽  
Tino Hausotte
Keyword(s):  
Computed Tomography ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Measurement Process ◽  
Initial Contour ◽  
Process Step ◽  
Edge Detection Algorithm ◽  
X Ray ◽  
Starting Point ◽  
X Ray Computed

AbstractSurface determination is an essential step of the measurement process in industrial X-ray computed tomography (XCT). The starting point of the surface determination process step is a single grey value threshold within a voxel volume in conventional surface determination methods. However, this value is not always found in the reconstructed volume in the local environment of the surface of the measurement object due to various artefacts, so that none or incorrect surfaces are determined. In order to find surfaces independently of a single grey value, a three-dimensional approach of the initial contour determination based on a Prewitt edge detection algorithm is presented in this work. This method is applied to different test specimens and specimen compositions which, due to their material or material constellation, their geometric properties with regard to surfaces and interfaces as well as their calibrated size and length dimensions, embody relevant properties in the examination of joining connections. It is shown that by using the surface determination method in the measurement process, both a higher metrological structure resolution and interface structure resolution can be achieved. Surface artefacts can be reduced by the application and it is also an approach to improved surface finding for the multi-material components that are challenging for XCT.

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 Texture Construction Edge Detection Algorithm

2019 ◽  
Vol 9 (5) ◽  
pp. 897 ◽  
Author(s):  
Shou-Cih Chen ◽  
Chung-Cheng Chiu
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Detection Algorithm ◽  
Edge Information ◽  
Edge Detection Algorithm ◽  
Detection Technology ◽  
Texture Change ◽  
Object Edge ◽  
Edge Detection Method ◽  
Threshold Setting

The edge detection algorithm is the cornerstone of image processing; a good edge detection result can further extract the required information through rich texture information and achieve object detection, segmentation, and identification. To obtain a rich texture edge detection technology, this paper proposes using edge texture change for edge construction and constructs the edge contour through constructing an edge texture extension between the blocks to reduce the missing edge problem caused by the threshold setting. Finally, through verification of the experimental results, the proposed method can effectively overcome the problem caused by unsuitable threshold setting and detect rich object edge information compared to the adaptive edge detection method.

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