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In this paper we study a possible solution to a problem existing in the cork industry: the cork stopper/disk classification according to their quality using a visual inspection system. Cork is a natural and heterogeneous material, therefore, its automatic classification (usually, seven different quality classes exist) is very difficult. The solution proposed in this paper shows all the stages made in our study: quality discriminatory features selection and extraction, texture analysis, analysis of different (global and local) automatic thresholding techniques and possible classifiers. In each stage we have given more importance to the study of those aspects that we think could influence the cork quality. In this paper we attempt to evaluate each of the stages in our solution to the problem of the cork classification in an industrial environment, and therefore, finding a way to justify the design of our final classification system. In conclusion, our experiments show that the best results are obtained by a system that works with the following features: total cork area occupied by defects (thresholding with heuristic fixed value 69), textural contrast, textural entropy and size of the biggest defect in the cork, all of them working in an Euclidean classifier. The obtained results have been very encouraging.

A SOLUTION FOR EVALUATING THE STOPPER QUALITY IN THE CORK INDUSTRY