Principles of image processing in machine vision systems for the color analysis of minerals

2014 ◽  
Author(s):  
Daria B. Petukhova ◽  
Elena V. Gorbunova ◽  
Aleksandr N. Chertov ◽  
Valery V. Korotaev
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Color Analysis ◽  
Vision Systems

Parallel processing in machine vision

Robotica ◽  
1984 ◽  
Vol 2 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Stanley R. Sternberg
Keyword(s):  
Image Processing ◽  
Parallel Processing ◽  
Machine Vision ◽  
Mathematical Morphology ◽  
Programming Language ◽  
Parallel Processor ◽  
Vision Systems ◽  
Processor Architectures ◽  
Image Flow ◽  
Industrial Part

SUMMARYMachine vision systems incorporating highly parallel processor architectures are reviewed. A new processor architecture, the image flow computer, is presented in detail. An interactive image processing programming language based on mathematical morphology is then presented. A detailed example of the use of the system for the inspection of a particular industrial part concludes the presentation.

scholarly journals Small flexible automated system for monitoring Caenorhabditis elegans lifespan based on active vision and image processing techniques

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joan Carles Puchalt ◽  
Antonio-José Sánchez-Salmerón ◽  
Eugenio Ivorra ◽  
Silvia Llopis ◽  
Roberto Martínez ◽  
...  
Keyword(s):  
Image Processing ◽  
Caenorhabditis Elegans ◽  
Culture Media ◽  
Active Vision ◽  
Automated System ◽  
Rank Test ◽  
P Value ◽  
Vision Systems ◽  
C Elegans ◽  
Processing Techniques

AbstractTraditionally Caenorhabditis elegans lifespan assays are performed by manually inspecting nematodes with a dissection microscope, which involves daily counting of live/dead worms cultured in Petri plates for 21–25 days. This manual inspection requires the screening of hundreds of worms to ensure statistical robustness, and is therefore a time-consuming approach. In recent years, various automated artificial vision systems have been reported to increase the throughput, however they usually provide less accurate results than manual assays. The main problems identified when using these vision systems are the false positives and false negatives, which occur due to culture media changes, occluded zones, dirtiness or condensation of the Petri plates. In this work, we developed and described a new C. elegans monitoring machine, SiViS, which consists of a flexible and compact platform design to analyse C. elegans cultures using the standard Petri plates seeded with E. coli. Our system uses an active vision illumination technique and different image-processing pipelines for motion detection, both previously reported, providing a fully automated image processing pipeline. In addition, this study validated both these methods and the feasibility of the SiViS machine for lifespan experiments by comparing them with manual lifespan assays. Results demonstrated that the automated system yields consistent replicates (p-value log rank test 0.699), and there are no significant differences between automated system assays and traditionally manual assays (p-value 0.637). Finally, although we have focused on the use of SiViS in longevity assays, the system configuration is flexible and can, thus, be adapted to other C. elegans studies such as toxicity, mobility and behaviour.

Study on the Measuring and Positioning of the Rim Valve Hole Based on Machine Vision

2014 ◽  
Vol 711 ◽  
pp. 333-337 ◽  
Author(s):  
Fang Wang ◽  
Chao Kun Ma ◽  
Shan Qiang Dai ◽  
Chang Chun Li
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Measurement Method ◽  
Ccd Camera ◽  
Servo Motor ◽  
Processing Characteristic ◽  
Linear Ccd ◽  
Hole Position ◽  
And Control

The author has designed a visual workbench to realize that the rim can rotate with the workbench. Meanwhile, the linear CCD camera records the rim’s circumference. The paper has explored the measurement method of getting the rim valve hole position using machine vision. The system can calculate the position of rim-hole and control the servo motor by image processing, characteristic recognizing and measuring to locate the position of wheel-hole automatically. And the paper has verified the accuracy of the method by experiments.

scholarly journals Machine Vision Systems for Plant Growth Measurement and Modeling

2006 ◽  
Vol 44 (3) ◽  
pp. 181-187 ◽  
Author(s):  
Ta-Te LIN ◽  
Chung-Fang CHIEN ◽  
Wen-Chi LIAO ◽  
Kuo-Chi CHUNG ◽  
Jen-Min CHANG
Keyword(s):  
Plant Growth ◽  
Machine Vision ◽  
Vision Systems ◽  
Growth Measurement ◽  
Plant Growth Measurement
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