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Based on machine vision fiber head surface defect detection applied research

Author: LiChunTao
Tutor: KangBo
School: University of Electronic Science and Technology
Course: Pattern Recognition and Intelligent Systems
Keywords: machine vision surface defects detection concentricity detection scratches detection
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 74
Quote: 0
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Abstract


Optical fiber connector, as the necessary equipment which connects two optical fibers, its surface defects can make a head high loss when light signal that transmit in optical fiber through optical fiber connector and affect the performance of the optical fiber network. The traditional method of optical fiber connector surface defects detection, mainly completed by artificially responsible for, has been unable to meet demand. In recent years, the system of product surface defects detection based on machine vision technology by its fast detection speed, high precision, no damage, and many other advantages plays a more and more important role in the modern industrial automation production.This paper mainly studies the surface defects detection method of optical fiber connector, which based on machine vision technology, including concentricity detection and scratches detection two aspects. In surface concentricity detection of optical fiber connector, the paper fit the surface concentricity of optical fiber connector by position of the center of internal circle in many surface images of optical fiber connector which are obtained through the microscope when the optical fiber connector is rotated. In order to accurately find out the position of the center of internal circle in each surface image of optical fiber connector, the paper will first get edge mask of internal circle by binary, internal circle contour extraction and morphological processing, and then combine Canny edge detection to obtain candidate edge pixels of the internal circle, then select pixels which can best show the edge of the internal circle from the candidate edge pixels through random sampling consensus estimation , further fit edge sub-pixel positions of the internal circle through three Facet model, finally, fit the position of the center of the internal circle by the edge sub-pixel positions of it.In surface scratches detection of optical fiber connector, the paper first grow to line-support regions according to feature of gradient of pixels which are in the scratches in surface gray image of optical fiber connector. Then each line-support region can be approximated by a proper rectangular. In order to reducing by mistake detection and accurate positioning scratches, this paper will verify each rectangular approximating line-support region. Finally, according to the distance and direction angle of scratches, combine the scratches belonging to the same scratches into one scratch.Finally, according to the studies of surface concentricity detection and scratches detection of optical fiber connector in this paper, the surface concentricity detection experiment and surface scratches detection experiment are implemented. And then the experiment results are carefully analyzed. The experiment results show that the surface defects detection method of optical fiber connector studied in this paper which based on machine vision technology, can rapidly and accurately detect the surface concentricity and scratches of optical fiber connector, and can be applied to practical projects of the surface defects detection of optical fiber connector. Therefore, the expected purpose is reached.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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