An automated system for contact lens inspection

Authors:
A. I. Bazin;T. Cole;B. Kett;M. S. Nixon
Affiliations:
School of Electronics and Computer Science, University of Southampton, Southampton, United Kingdom;Neusciences, Unit 2, Lulworth Business Centre, Totton, Southampton, United Kingdom;Neusciences, Unit 2, Lulworth Business Centre, Totton, Southampton, United Kingdom;School of Electronics and Computer Science, University of Southampton, Southampton, United Kingdom
Venue:
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Year:
2006

Citing 8
Cited 1

A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Simplifying decision trees

International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Randomized Hough transform: improved ellipse detection with comparison

Pattern Recognition Letters
Direct Least Square Fitting of Ellipses

IEEE Transactions on Pattern Analysis and Machine Intelligence
Constrained Hough transforms for curve detection

Computer Vision and Image Understanding
A Robust Snake Implementation; A Dual Active Contour

IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Technique for Ellipse Detection Using Restricted Randomized Hough Transform

ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Gait Verification Using Probabilistic Methods

WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01

An innovative blemish detection system for curved LED lenses

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.01

Visualization

Abstract

This paper describes a novel method for the industrial inspection of ophthalmic contact lenses in a time constrained production line environment. We discuss the background to this problem, look at previous solutions and relevant allied work before describing our system. An overview of the system is given together with detailed descriptions of the algorithms used to perform the image processing, classification and inspection system. We conclude with a preliminary assessment of the system performance and discuss future work needed to complete the system.