We deald with an industrial problem: a jewelry stones classification. The stones are represented by their camera images. The goal of the contract was to evaluate stones into two (or more) specified classes according to their quality. Given requirements include very high processing speed and success rate of the classification. The goal of this paper isto publish a report of this contract and show a way how this task can be solved. We aim to usage of machine learning with respect to the image processing. We also design own learning and classification algorithm and answer the question if there is a place for a new machine learning algorithm; so we compared proposed algorithmwith 81 state-of-the-art machine learning methods.
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