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.

scholarly journals Measurements of surface flatness distortions using machine vision inspection system

Mechanik ◽  
2017 ◽  
Vol 90 (12) ◽  
pp. 1155-1156
Author(s):  
Anna Zawada-Tomkiewicz ◽  
Dariusz Tomkiewicz ◽  
Lesław Wilk
Keyword(s):  
Thermal Treatment ◽  
Machine Vision ◽  
Vision System ◽  
Float Glass ◽  
Inspection System ◽  
Vision Inspection ◽  
Surface Flatness ◽  
Machine Vision Inspection

The use of a vision system for evaluating the flatness distortion of float glass under thermal treatment in a horizontal process is presented. The possibility of evaluation of such parameters as overall bow, roller wave and edge lift was analyzed for a pane of glass taken from production.

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.

Intelligent Vision Inspection System for IC Engine Head: An ANN Approach

2012 ◽  
Vol 479-481 ◽  
pp. 2242-2245 ◽  
Author(s):  
Rajesh Kanna ◽  
Manikandan Saravana
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Back Propagation ◽  
Engine Block ◽  
Inspection System ◽  
Back Propagation Algorithm ◽  
Ic Engine ◽  
Vision Inspection ◽  
System Module ◽  
Artificial Neural Network Ann

A machine vision system based on Artificial Neural Network (ANN) for inspection of IC Engine block was developed to identify the misalignment and improper diminishing of holes in the IC Engine block. The developed machine vision and ANN module is compared with the commercial MATLAB® software and found results were satisfactory. This work is broadly divided into four stages, namely Intelligent inspection module, Machine Vision module, ANN module and Expert system module. A system with a camera was used to capture the various segments of head of the IC Engine block. The captured bitmap format image of IC Engine block has to be filtered to remove the noises present while capturing and the size is also altered using SPIHT method to an acceptable size and will be given as input to ANN. Generalized ANN with Back-propagation algorithm was used to inspect the IC Engine block. ANN has to be trained to provide the inspected report.

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.

Research on Inspection System Formation of Cells in Gravure Cylinder Base on Machine Vision

2010 ◽  
Vol 174 ◽  
pp. 207-210
Author(s):  
Zi Fen He ◽  
Zhao Lin Zhan ◽  
Yin Hui Zhang
Keyword(s):  
Machine Vision ◽  
Production Management ◽  
Process Analysis ◽  
Image Sensor ◽  
Inspection System ◽  
Canny Operator ◽  
Vision Inspection ◽  
Sobel Operator ◽  
Dark Tone ◽  
Machine Vision Inspection

This paper presents a machine vision inspection system to detect deformation of cells in the process of gravure manufacturing, which can provide real-time reporting and detail testing process analysis and find problems and make adjustments to track the production process, more conducive to scientific production management. The formation of cells of gravure machine vision inspection system is able to change analog signal into digital signal of gravure image. We have applied the MATLAB image processing software to read the experiment images and histogram equalization. The edge of cells is extracted by using of Sobel operator and Canny operator. We use different thresholds and experimental sigma values that compare to experimental results. It is found that extraction using the Canny operator is better than Sobel operator. Canny edge extraction operator is best when the value of sigma is 16. According to the image used in this research to determine the standard cells carving the value of gaps d0 equals 125, the value of dark tone s0 equals 394, so its standard value of gaps and dark tone are d0 ± 10 and s0 ± 10. The value of gravure outlets gaps and dark tone are measured, while d and s is in the scope of standard range, which the output 1 of the cells determined to pass and the output 0 deemed to fail. We propose two solutions of cells deformation gravure machine vision inspection system. Through analysis and comparison of performance and economic of the lighting and image sensor, the final implementation of the program is identified.

Machine Vision Inspection of In Vitro Diagnostic Kits

2013 ◽  
Vol 753-755 ◽  
pp. 2164-2169
Author(s):  
Jiang Ping Mei ◽  
Yi Liu
Keyword(s):  
Machine Vision ◽  
Surface Defects ◽  
Detection Threshold ◽  
Inspection System ◽  
Strip Surface ◽  
Diagnostic Kits ◽  
Vision Inspection ◽  
In Vitro Diagnostic ◽  
Machine Vision Inspection

A machine vision-based inspection system was proposed to inspect the defects of in-vitro diagnostic kits in the production line. The proposed system consisted of two sub-systems, which inspect the strip surface defects and strip assembly defects respectively. The procedure to inspect five types of major defects was determined by the application of image processing and analysis techniques such as image enhancement, edge detection, threshold segmentation, and morphology. The proposed system was implemented using 300 defect samples. Experimental results show the proposed system is effective and efficient.

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