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Raindrop size distribution data detection system based on machine vision technology

Author: GaoXueLiang
Tutor: HanLiQiang
School: Changchun University of
Course: Mechanical and Electronic Engineering
Keywords: Complex cascade transform Particle identification Diameter statistics Mathematical Morphology
CLC: TP274
Type: Master's thesis
Year: 2010
Downloads: 51
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Abstract


Present stage raindrop size distribution data detection by artificial means to achieve this process is complicated, labor intensity , long testing cycle , low efficiency , missed , the probability of false detection , it is difficult to be controlled , and with a certain subjective sex . With the rapid development of computer technology and a variety of vision algorithms , the application of machine vision technology has been more and more widely . Machine vision technology used in the raindrop size distribution data detection process , with its advantages of non-contact, fast , good stability , greatly improve the efficiency of detection . Issues of practical application , carried out the research work of the raindrop size distribution data detection , image processing of raindrop size distribution data is the main content of the research , including : effective sampling area for the image of raindrop size distribution data , raindrops particle identification , adhesion the raindrops particles split and particle size statistics , and related technologies . In the process of image preprocessing , we propose a the composite cascade transformation and interpolation method of combining , for the effective sampling area of the raindrop size distribution data image , and effectively solve the distortion in the image transformed to improve the identification of particles accuracy ; nonlinear filtering method , the raindrops sputtering do not mind small particles filtered out , reducing the raindrop size image feature extraction complexity, improve processing speed ; Otsu ( Otsu method) and the threshold value of the evaluation function , effectively improve the accuracy of raindrop particle identification ; integrated use of distance transform , morphological reconstruction and watershed segmentation algorithm, the adhesion of raindrops particle separation ; paper, curve fitting , regression analysis and morphological combination of methods to obtain the raindrops particles and stain pixels corresponding to the relationship between , on this basis , the statistical classification of raindrop size . The test results show that the machine vision , image processing of raindrop size , can quickly and accurately raindrop size particles split , statistics , with high efficiency , easy automated , there is a good practical raindrop size distribution data detection A new solution .

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