Paper
22 May 2003 Automated visual inspection for polished stone manufacture
Author Affiliations +
Proceedings Volume 5011, Machine Vision Applications in Industrial Inspection XI; (2003) https://doi.org/10.1117/12.477511
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States
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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Melvyn L. Smith and Lyndon N. Smith "Automated visual inspection for polished stone manufacture", Proc. SPIE 5011, Machine Vision Applications in Industrial Inspection XI, (22 May 2003); https://doi.org/10.1117/12.477511
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KEYWORDS
Surface finishing

Polishing

Inspection

Machine vision

3D image processing

Data acquisition

Reflectivity

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