Development of an automated classification system .. (PROVIPS)
Development of an automated classification system for polished stone slabs and tiles
Start date: 01 Oct 2008,
End date: 31 Mar 2011
"Limitations in quality control performance represent an obstacle in evolution of the Stone Processing Industry. A way to automated surface analysis is pivotal in realising improved product quality and greater operational efficiency thus reducing the environmental impact of stone processing and reducing product’s time to market. Such improvements are considered to be of major significance to the European SME proposers to secure existing markets and to develop new opportunities. This project aims to consolidate the technical know-how and bridge the technological gaps to allow the development of an automated classification system for ornamental stone slabs and tiles (PROVIPS) based on the development of an innovative spectral sensor to be used within a new type of spectral camera. Such a capability will help the European stone sector by providing a versatile classification tool for lot appearance standardization according to end-user requirements thus enhancing distribution networks by way of greater acceptability of the product and higher productivity at the stone processing stage. Moreover, the new sensor will allow European Vision System Sector to get the chance to renew their offer on existing markets and to find new markets as well. Basing on the experience gained by the partners the following paths for research and development will be scouted: 1.design and development of the ad-hoc spectral sensor enabling the use of spectral imaging techniques. This sensor will acquire colour according to human perception and will allow an innovative approach to pattern recognition; 2.development of goniometric probe for the multi-directional spectral characterization of the surface to allow multiple position inspection as made by human specialized observer; 3.rationalization of human classification process and development of standard quality and grading features to guide the development of classification algorithms in order to solve the complexity of patterns of natural stone"
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