Detection of the Tool Wear Condition Based on the Computer Image Processing

2008 ◽  
Vol 375-376 ◽  
pp. 553-557
Author(s):  
Ya Liang Wang ◽  
Shi Ming Ji ◽  
Li Zhang ◽  
Shou Song Jin ◽  
Yong Chen
Keyword(s):  
Image Processing ◽  
Tool Wear ◽  
Computer Image ◽  
Cutting Tool ◽  
Detection Method ◽  
Detection System ◽  
High Quality ◽  
Computer Image Processing ◽  
Occurrence Matrix ◽  
Wear Condition

The tool wear detection system based on the image processing and computer vision has better study value and foreground. The paper brings forward the detection method of the tool wear condition, which solves the two main problems. Firstly, gets the high quality images by fuzzy restoration arithmetic. Because the cutting tool is always at the movement state during the cutting, the real-time collected sequence images by CCD sensor are blurred with noise. Then, obtains the character parameter uniformity Q2 by calculating gray co-occurrence matrix, which can distinguish the cutting tool is weared or not weared. The experimental results indicate that detection of the tool wear condition by computer image processing reach our aim.

Computer-Aided Interpretation of Coronary Cineangiograms

1992 ◽  
Vol 33 (1) ◽  
pp. 6-9 ◽  
Author(s):  
T. Sugahara ◽  
Y. Yamagihara ◽  
N. Sugimoto ◽  
K. Kimura ◽  
K. Awano ◽  
...  
Keyword(s):  
Image Processing ◽  
Computer Image ◽  
Detection Rate ◽  
Detection Method ◽  
Visual Interpretation ◽  
Detection Rates ◽  
Computer Image Processing ◽  
Computer Aided ◽  
Computer Recognition ◽  
Stenotic Lesions

To accurately diagnose stenotic lesions on coronary cineangiograms, an automatic detection method using computer image processing was developed. We evaluated its accuracy by comparing the results of computer-aided interpretation (CAI) with those obtained independently by 3 observers. Evaluation was performed on 129 segments from 27 arteries visualized on angiograms obtained in 18 patients. The detection rates of stenosis of the 3 observers by pure visual interpretation were 7.0%, 27.9%, and 17.1%, and using CAI 40.0%, 42.6%, and 47.3%. By computer recognition alone, a detection rate of 51.9% was achieved. The agreement by at least 2 observers (consensus) on the sites with lesions was 41.1% while the consensus of computer recognition regarding the sites with lesion was 40.3%. Therefore, our findings indicated that computer recognition of cineangiograms is likely to result in overdetection of lesions. However, all 3 observers detected stenotic lesions better with CAI than with pure visual interpretation. Accordingly, CAI may improve the reliability of cineangiographic diagnosis.

Image detection and parameterization for different components in cross-sections of radial tires

2021 ◽  
pp. 095440702110236
Author(s):  
Chen Liu ◽  
Yude Dong ◽  
Yanli Wei ◽  
Jiangtao Wang ◽  
Hongling Li
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Cross Sections ◽  
Digital Image ◽  
Detection Method ◽  
Detection System ◽  
Practical Significance ◽  
Vehicle Safety ◽  
Wire Steel ◽  
Good Detection

The internal structure analysis of radial tires is of great significance to improve vehicle safety and during tire research. In order to perform the digital analysis and detection of the internal composition in radial tire cross-sections, a detection method based on digital image processing was proposed. The research was carried out as follows: (a) the distribution detection and parametric analysis of the bead wire, steel belt, and carcass in the tire section were performed by means of digital image processing, connected domain extraction, and Hough transform; (b) using the angle of location distribution and area relationship, the detection data were optimized through coordinate and quantity relationship constraints; (c) a detection system for tire cross-section components was designed using the MATLAB platform. Our experimental results showed that this method displayed a good detection performance, and important practical significance for the research and manufacture of tires.

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