
Proceedings Paper
Automated visual inspection for polished stone manufactureFormat | Member Price | Non-Member Price |
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Paper Abstract
Increased globalisation of the ornamental stone market has lead to increased competition and more rigorous product quality requirements. As such, there are strong motivators to introduce new, more effective, inspection technologies that will help enable stone processors to reduce costs, improve quality and improve productivity. Natural stone surfaces may contain a mixture of complex two-dimensional (2D) patterns and three-dimensional (3D) features. The challenge in terms of automated inspection is to develop systems able to reliably identify 3D topographic defects, either naturally occurring or resulting from polishing, in the presence of concomitant complex 2D stochastic colour patterns. The resulting real-time analysis of the defects may be used in adaptive process control, in order to avoid the wasteful production of defective product. An innovative approach, using structured light and based upon an adaptation of the photometric stereo method, has been pioneered and developed at UWE to isolate and characterize mixed 2D and 3D surface features. The method is able to undertake tasks considered beyond the capabilities of existing surface inspection techniques. The approach has been successfully applied to real stone samples, and a selection of experimental results is presented.
Paper Details
Date Published: 22 May 2003
PDF: 10 pages
Proc. SPIE 5011, Machine Vision Applications in Industrial Inspection XI, (22 May 2003); doi: 10.1117/12.477511
Published in SPIE Proceedings Vol. 5011:
Machine Vision Applications in Industrial Inspection XI
Martin A. Hunt; Jeffery R. Price, Editor(s)
PDF: 10 pages
Proc. SPIE 5011, Machine Vision Applications in Industrial Inspection XI, (22 May 2003); doi: 10.1117/12.477511
Show Author Affiliations
Melvyn L. Smith, Univ. of the West of England (United Kingdom)
Lyndon N. Smith, Univ. of the West of England (United Kingdom)
Published in SPIE Proceedings Vol. 5011:
Machine Vision Applications in Industrial Inspection XI
Martin A. Hunt; Jeffery R. Price, Editor(s)
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