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Research And Realization Of Visible Particle Detection System For Pharmaceutical Glass Bottle Infusion

Posted on:2016-01-23Degree:MasterType:Thesis
Country:ChinaCandidate:B ZhangFull Text:PDF
GTID:2311330473965805Subject:Electronic Science and Technology
Abstract/Summary:PDF Full Text Request
Pharmaceutical glass bottle large transfusion is one of the five important preparations pharmaceutical industry in China. They are frequently-used drugs in medical institutions and play a very important role in modern clinic. However, some visible foreign substances may appear in the bottle infusion uring the processes of producing, filling and packaging. These foreign substances will turn out to be a serious threat to patients. At present, most of the Chinese pharmaceutical manufacturers adopt the traditional manua l inspection. Obviously, the manual inspection is slow, complex and unreliable, and usually brings in extra pollution to the drugs, thus is unsafe, Can't guarantee the quality of the product fundamentally, but also can't meet the production requirements of high-speed production line.Firstly, the background and significance of the glass bottle large transfusion visual detection system research has been proposed in this paper. Combined with the application of infusion drugs production process and machine vis ion technology in the field of industrial detection, analysis the research status of medical infusion visual detection technology and equipment at home and abroad, and then put forward the overall design of glass bottle large transfusion visible foreign ma tter in the visual detection system according to the characteristics of visible foreign substances in transfusion system are introduced in detail light source and lighting, camera industry, mechanical and electrical control system and detection system software architecture and key technologies.Secondly, the continuous images which obtain moving foreign bodies are pretreated, and its main purpose is for the interference of the background noise suppression imaging. According to the interference noise, this paper presents a kind of adaptive median filter algorithm, with traditional algorithms, the algorithm can remove noise and preserve edges and details better and reduce image processing after the fuzzy degree, can be effective in the region detection liquid image noise filtering.Thirdly, when the detection system run, system of mechanical vibration is inevitable, between industrial camera and the transfusion bottle can 't guarantee absolute synchronization, thus continuously acquires the transfusion between sequential images will appear deviation, must be on the acquisition of the consecutive frames image registration processing, can accurately detect visible foreign matter, this paper proposes based on the dyadic wavelet and scale invariant feature transform(SIFT image registration algorithm. In this algorithm, the original image and the template image of dyadic wavelet decomposition to obtain the coarse scale image smoothing; reuse thedog feature point detector for detecting the key points of image. Then the Euclidean distance of the feature points matching. Experimental results show that the proposed algorithm can not only reduce the calculation amount of image feature points matching, but also improve the image feature points matching rate, thus enhancing the image registration algorithm is practical and effective. Research and implementation of inter secondary difference points and gray energy accumulation combination of foreign objects detection method based on, effective discharged various trace interfer ences that may exist in the bottle, accurately detect the infusion of foreign objects.Finally, a large infusion of visible particles in visual detection software is developed based on the above technology. Design the user information module, control module and software detection module, and introduces the development and realization process of each function module of system software.
Keywords/Search Tags:Infusion bottles, Visual detection, Image registration, Image denoising, Foreign partical detection
PDF Full Text Request
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