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The Research on Veneer Peeling Image Defect Inspection Technology Based on PDE

Author: YuLinZuo
Tutor: WangAChuan
School: Northeast Forestry University
Course: Applied Computer Technology
Keywords: Peeled veneer Defect detection Extended C-V model AOS algorithm Background fill
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 18
Quote: 0
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Abstract


With the rapid development of computer technology and artificial intelligence technology, image processing technology in recent years has made tremendous progress, partial differential equations are also very widely in the field of image processing applications. In industrial, military and medical developed various models for image processing, these human work and life have brought great convenience. This article briefly describes the research background of the image processing method of partial differential equations and development status at home and abroad, in-depth study of image segmentation method based on partial differential equations and image segmentation CV model system. Veneer of gray-scale images and color images of defects detected compared with background fill. By computer analysis and processing to achieve the automatic detection of the image of the of peeled veneer surface defects, thereby reducing the labor intensity of the operator, and improve the timber out of wood rate and production efficiency, provide the basis for peeled veneer surface image defect detection. According to the characteristics of the veneer surface defects using the CV model image segmentation, get Setsuko defects outline. For CV model problems that need to re-initialize the iterative process, the introduction of another energy function control signed distance function to solve computing complexity problem. CV model in the numerical calculation using the Euler method makes the problem of low computational efficiency, the introduction of the semi-implicit AOS method, solve algorithms restrictions on the time step, and experimental results show that this method to improve the segmentation speed effect. For the the peeling veneer surface defects in a wide range of distribution range, the introduction of the background fill technology. The use of the background fill technology can reduce the difference between the target and the background characteristics to achieve the effect of narrowing the target range of the identification veneer defects. The format of this paper AOS improved CV model combined with the background filled detect veneer surface defects, and experimental verification through Matlab. The experimental results show that this method can quickly and effectively divides Veneer surface defects, thereby improving the speed of the whole algorithm. Slow, articulated defects border grayscale transform using grayscale image segmentation method articulated defect segmentation result is not satisfactory, the CV model vector image, the color image processing as a whole image, make full use of the image information, solve the problem of articulated defect recognition. AOS format color images improved CV model combined with the background fill technology, not only can identify the live Festival defects, but also to identify the the peeled veneer color image defects. Partial differential equations as an emerging technology in image processing, image processing will play an increasingly important role. Starting from the partial differential equation model of CV CV model was improved with the addition operator splitting algorithms and background fill the combination of technology, improve and enhance existing CV algorithm, defect recognition of peeled veneer surface image The technology also has a significant role in promoting.

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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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