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Application Research of Machine Vision Technology on Empty Bottle Inspector

Author: ChenXiGuang
Tutor: XuLeNian
School: Shandong University of Science and Technology
Course: Measuring Technology and Instruments
Keywords: Empty Bottle Inspection Machine Machine Vision CCD camera Image processing
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 61
Quote: 0
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Abstract


Beer producers more and more attention to product quality, more and more enterprises in the canned production line using a variety of automatic test equipment, in order to improve the reliability of the detection. Empty Bottle Inspection of the traditional canned line detection of artificial fluorescent light box. But in modern high-speed canning line, due to reasons such as visual fatigue, artificial fluorescent light box detector alone can not guarantee the reliability, and the mouth of the bottle and the bottom of the bottle of beer bottle two important parts prone to undetected caused some leakage cylinders and bottom of the bottle stolen property bottles into the market and cause damage to the corporate image abroad \beer producers must fulfill obligations. Foreign bottles online detection system based on image processing technology has been relatively mature and there is a large number of products put on the market, such as: Germany HEUFT KRONES, Miho, and Japan KTS etc.. Relatively backward country in this regard, and now there is no comprehensive and reliable system to market. The main subject of Empty Bottle Inspection Machine part of image processing hardware and software involved the following aspects: image acquisition equipment selection, in order to ensure the completion of the high-speed production line running instantly targeted imaging, the selection of high resolution, high contrast and high frame rate CCD camera. The camera work can be completed within a time of 1/60 sec in the trigger mode and asynchronous reset mode, the output of full-pixel. Optical lighting technology combined with high-quality, clear imaging can be done on a beer bottle mouth, bottom, and lay a good foundation for the subsequent image processing and analysis; image processing is divided into image pre-processing, edge detection, binarization processing erosion and dilation, contour tracking algorithm and image positioning six steps. Median filter filter out noise, taken to gain compensation enhanced image and edge detection using Canny operator, you can get a clear continuous edge grayscale scanning image boundaries, using the method of least squares fitting center and radius. The connected domain search algorithms to detect defects, integrated decision unless the tainted interference. Bottle and the bottom of the bottle defect detection. The accurate positioning of the image of the mouth and the bottom is a prerequisite for detection of defects, relatively clear under the bottle annular edge, interference edge is relatively small features, on the mouthpiece of the circle center positioning using the edge detection combined with the method of least squares fitting circle way to the center and radius. The bottom annular edge of obvious interference more edges and there is the influence of the non-slip pattern, is detected by detecting the non-slip pattern of mutation point of the inner edge gray boundary, by the least squares method to fit the center and radius for the bottom by detecting if there is more than qualified black the circumference or white circumference of the length to determine the bottom of the bottle is qualified.

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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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