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Research and Integration on Web Inspection System Based on Machine Vision

Author: ChenWenKai
Tutor: HuMuYi
School: Nanjing Forestry University
Course: Pulp and Paper Engineering
Keywords: Web Inspection Machine Vision Image processing Feature Extraction Hough transform
CLC: TP274.4
Type: Master's thesis
Year: 2009
Downloads: 120
Quote: 6
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Abstract


With the rise of the breadth and speed of the machine , the traditional appearance of the paper diseases rely on the artificial visual inspection paper has been difficult to meet the needs of the production process . The emergence of paper defect detection system based on machine vision technology not only greatly improve the efficiency of detection , online analysis and control . In this paper, intelligent image sensor DVT Legend530 capture images , paper the disease -line detection analog papermaking process , developed a paper the disease -line detection experimental system . The paper selected holes, dirty spots, fold three representative paper diseases as objects , mainly digital image preprocessing algorithm suitable for applications in paper the disease -line detection system , including the the denoising threshold segmentation , edge detection , mathematical morphological operations , etc. ; according to the characteristics of paper defects image dynamic dual - threshold segmentation method based on gray-scale experience , used to detect high - contrast paper disease ; discuss the conventional image feature extraction method in the application of the paper defect detection system when the problems encountered and propose a Hough transform - based image feature extraction methods to address these issues through the analysis of the Hough transform space to extract the folds in the paper defect image characteristics and identify . Combined with the actual requirements of the production process of paper the disease -line detection algorithm based on using the Delphi software development platform , designed a set of paper defects image acquisition and transmission , image preprocessing , image feature extraction and recognition , paper disease online monitoring , historical data query functions paper defect detection experimental system , and system testing and analysis . Finally, for inadequacies study , the follow-up study recommendations .

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Data processing, data processing system > Centralized testing and roving detection system
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