By Topic

Automatic inspection system using machine vision

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Khan, U.S. ; Dept. of Mechatronics, Nat. Univ. of Sci. & Technol., Rawalpindi ; Iqbal, J. ; Khan, M.A.

Man from the beginning of time, tried to automate things for comfort, accuracy, precision and speed. Technology advanced from manual to mechanical and then from mechanical to automatic. Vision based applications are the products of the future. Machine vision systems integrate electronic components with software systems to imitate a variety of human functions. This paper describes current research on a vision based inspection system. A computer using a camera as an eye has replaced the manual inspection system. The camera is mounted on a conveyor belt. The main objective is to inspect for defects, instead of using complicated filters like edge enhancement, and correlation etc. a very simple technique has been implemented. Since the objects are moving over the conveyor belt so time is a factor that should be counted for. Using filters or correlation procedures give better results but consume a lot of time. The technique discussed in this paper inspects on the basic pixel level. It checks on the basis of size, shape, color and dimensions. We have implemented it on five applications and the results achieved were good enough to prove that the algorithm works as desired

Published in:

Applied Imagery and Pattern Recognition Workshop, 2005. Proceedings. 34th

Date of Conference:

1-1 Dec. 2005