scholarly journals Automated Tablet Quality Assurance and Identification for Hospital Pharmacies

2011 ◽  
Vol 57 (2) ◽  
pp. 153-158
Author(s):  
Zenon Chaczko ◽  
Anup Kale
Keyword(s):  
Quality Assurance ◽  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Inspection System ◽  
Machine Vision System ◽  
Manual Sorting ◽  
Recognition Ability ◽  
Hospital Pharmacies ◽  
Evolution Algorithm

Automated Tablet Quality Assurance and Identification for Hospital PharmaciesThe tablet quality checking and identification in hospital pharmacies is done manually and does not use any automated solution. Manual sorting and handling makes this activity laborious and error-prone. This paper describes a low cost solution that is characterised by a small size of the infrastructure involved. Discussed are design and implementation details of Tablet Inspection System based on Machine Vision. The described process uses a dedicated sequence of operation to perform dispensing, scanning and sorting using mini factory setup. Machine Vision System uses a novel Genetic Evolution algorithm. The algorithm provides robust and scalable output. Due to its versatile nature and easy shape recognition ability the approach can be easily adapted to a large variety of medical tablets. The proposed solution attempts to follow the concept of single objective with multiple optima in GA that is designed to scan multiple number of tablets in one cycle of operation.

Development of Ultralow-Cost Machine Vision System

2017 ◽  
Vol 11 (4) ◽  
pp. 629-637 ◽  
Author(s):  
Kenichi Endo ◽  
◽  
Teruyuki Ishiwata ◽  
Tomohiro Yamazaki
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Inspection System ◽  
Machine Vision System ◽  
Quality Improvements ◽  
Automobile Manufacturing ◽  
Vision Inspection ◽  
The Cost ◽  
Machine Vision Inspection

This paper reports on the development of a low-cost machine vision inspection system to promote the wide employment of the system and foster further quality improvements in automobile manufacturing. The machine vision system consists of a camera that takes images of an inspection target, lighting to ensure appropriate illuminance, and a controller that analyzes the images and gives inspection results. By optimizing the performance and using free software, we succeeded in the development of an ultralow-cost machine vision system for one tenth of the cost of commercially available factory automation machine vision systems. The development and results are introduced in this paper. The applicability of the ultralow-cost machine vision system platform to applications other than inspection is also discussed.

Automatic Inspection System of Small Plastic Gears Based on Machine Vision

2012 ◽  
Vol 522 ◽  
pp. 628-633 ◽  
Author(s):  
Jian Zhe Chen ◽  
Gui Tang Wang ◽  
Jian Qiang Chen ◽  
Xin Liang Yin
Keyword(s):  
Machine Vision ◽  
Template Matching ◽  
Vision System ◽  
Inspection System ◽  
Injection Molding Process ◽  
Automatic Inspection ◽  
Machine Vision System ◽  
Molding Process ◽  
Small Plastic ◽  
Plastic Gears

Small plastic gear is generally made by injection molding.But the injection molding process and mold have problems with missing tooth, shrink, more material, less material and inaccurate roundness and so on. Furthermore, using manual inspection will appear phenomenon of low efficiency, false detection and leak detection. To solve these problems, this paper introduces an automatic inspection system of small plastic gears based on machine vision. The system consists of feeding and sorting machine control system and machine vision inspection system of the gear defects. Mechanical control use digital servo control technology to achieve automatic nesting, feeding, positioning of gear workpiece, and depend on the inspection result of machine vision system to sort. After acquired gear image through a camera, Machine vision system uses median filtering, binarization, edge detection algorithms to process image. Then the system adopts template matching algorithm to obtain the inspection result and send the result to the sorting controller, which achieve automatic smart inspection of gear. The automatic inspection system has accurate, efficient, intelligent and other advantages.

Development of Machine Vision Positioning System of Magnetorheological Fluid (MRF) Actuator

2013 ◽  
Vol 470 ◽  
pp. 625-629
Author(s):  
A.B. Husaini ◽  
Ghazali Izzat ◽  
Samad Zahurin ◽  
Othman Rusli
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Feedback System ◽  
Magnetorheological Fluid ◽  
Fast Response ◽  
Positioning System ◽  
Machine Vision System ◽  
Vision Positioning ◽  
Magnetorheological Valve

Magnetorheological valve offers several advantages such as controllability, small in size and no moving part during operation. Thus, many researchers are working on developing an actuator based on this valve. However, this actuator required feedback system to improve it precision. This research is focusing on developing of machine vision based positioning system for MRF actuator. Image processing algorithms coded using Matlab software and directly connect to MRF valve controller. As a result, the system shows a fast response with processing time only 0.6 millisecond, system resolution is 0.1 millimeter and finally repeatability is 0.01. As a conclusion, the machine vision system are applicable for MRF actuator positioning system. This study is significant in order to developing a low cost and robust positioning system.

scholarly journals Implementation and potentials of a machine vision system in a series production using deep learning and low-cost hardware

Procedia CIRP ◽  
2020 ◽  
Vol 90 ◽  
pp. 611-616
Author(s):  
Hubert Würschinger ◽  
Matthias Mühlbauer ◽  
Michael Winter ◽  
Michael Engelbrecht ◽  
Nico Hanenkamp
Keyword(s):  
Deep Learning ◽  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Machine Vision System ◽  
Series Production

scholarly journals Vision-Based Surface Inspection System for Bearing Rollers Using Convolutional Neural Networks

2018 ◽  
Vol 8 (12) ◽  
pp. 2565 ◽  
Author(s):  
Shengping Wen ◽  
Zhihong Chen ◽  
Chaoxian Li
Keyword(s):  
Neural Network ◽  
Machine Vision ◽  
Convolutional Neural Network ◽  
Vision System ◽  
Inspection System ◽  
Mechanical Transmission ◽  
Surface Inspection ◽  
Machine Vision System ◽  
Factors Affecting ◽  
Bearing Rollers

Bearings are commonly used machine elements and an important part of mechanical transmission. They are widely used in automobiles, airplanes, and various instruments and equipment. Bearing rollers are the most important components in a bearing and determine the performance, life, and stability of the bearing. In order to control the surface quality of the rollers, a machine vision system for bearing roller surface inspection is proposed. We briefly introduced the design of the machine vision system and then focused on the surface inspection algorithm. We proposed a multi-task convolutional neural network to detect defects. We extracted the features of the defects through a shared convolutional neural network, then classified the defects and calculated the position of the defects simultaneously. Finally, we determined if the bearing roller was qualified according to the position, category, and area of the defect. In addition, we explored various factors affecting performance and conducted a large number of experiments. We compared our method with the traditional methods and proved that our method had good stability and robustness.

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