DocumentCode
3252593
Title
Dimentional inspection and feature recognition through machine vision system
Author
Bhattacharyya, Bidyut K.
Author_Institution
Mech. Eng. Dept., Bengal Eng. & Sci. Univ., Howrah, India
fYear
2010
fDate
29-31 Oct. 2010
Firstpage
511
Lastpage
514
Abstract
Automated computerized machine vision inspection, techniques can be used as a tooling for automated shape inspection in an advanced CIM environment so that real time, reliable, non-contact and non-destructive, and 100% quality measure activities can be achieved fruitfully. This paper develops a generic hardware system, software architecture and a technology-mix for product feature identification and measurement analysis of various machined parts/products. The feature analysis seeks to identify inherent characteristics of feature of an object found within the image frame. These characteristics are used to describe the object or the attributes of the object features, prior to subsequent task for classification of the same. The special features of such an inspection methodology include system which is (i) Micro-computer based; (ii) flexible and reprogrammable; (iii) likely to remain effective at the floor; (iv) ensure the highest possible goes to the customer and (v) very efficient.
Keywords
computer integrated manufacturing; computer vision; feature extraction; inspection; object recognition; production engineering computing; software architecture; CIM environment; automated computerized machine vision inspection; dimensional inspection; feature recognition; generic hardware system; measurement analysis; microcomputer based systerm; product feature identification; software architecture; Robots; Feature extraction; Image Processing; computer vision; online inspection; pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management (IE&EM), 2010 IEEE 17Th International Conference on
Conference_Location
Xiamen
Print_ISBN
978-1-4244-6483-8
Type
conf
DOI
10.1109/ICIEEM.2010.5646564
Filename
5646564
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