Amber Gemstones Sorting By Colour

Saulius Sinkevicius, Arunas Lipnickas, Kestas Rimkus

Abstract


The objective of this study is to create computer vision algorithms for autonomous multiclass identification of amber nuggets by their colour. By applying the proposed methods an automated production sorting system has been developed. This system can be used, for example in combination with conveyor systems, and in any other case that requires distinguishing objects of many classes in a high-rate flow of objects. In order to achieve this, the proposed system operates with colour features selection, algorithm for classifier training, grouping, and voting with reject option have been developed. The developed system has been used in an automated amber sorting line to increase the quantities of sorted amber nuggets. The applied algorithms gave 88.21 % as the highest accuracy for the amber nugget expert database consisting of 30 classes.

DOI: http://dx.doi.org/10.5755/j01.eie.23.2.17993


Keywords


Expert systems; image classification; image colour analysis; image texture analysis; machine vision

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Print ISSN: 1392-1215
Online ISSN: 2029-5731