The Research On Image Recognition Of Coal And Non-coal Based On Texture Analysis

Coal output and transport volume control system is great significance for solving the situation that the management of coal production industry is difficult and realizing the modernization management of the coal industry. In this paper, recognition of stowage(coal and non-coal) in coal transport volume control system of sources of coal production and transportation (ore production),settlement station and coal storage yard was studied. Digital image processing technology was used to study and achieve recognition algorithm of coal and non-coal automatic identification. The techniques and methods in this paper lay a solid foundation for further researching and applicationIn this paper, coal and non-coal recognition was different from the previous coal and non-coal separation recognition system. It was based on the specific application environments of coal production and transportation (ore production),settlement station and coal storage yard. Through the research and analysis of coal and non-coal image, and research and analysis the data of coal and non-coal textural property based on Gray-Level Co-Occurrence Matrix, summing up the coal grain property eigenvector. Through training and classification of the sample image by SVM, in this way can get a well recognize effect. Every material have its own textural property, make use of computer image processing technologies to finish the compute of coal and non-coal textural property, we can get the required grain property vector. We can judge the material if it is coal by classified the eigenvector got by SVM.The recognize method in this paper realized automatic recognition of coal and non-coal in coal yard. The experimental proof that we get the eigenvector based on image gray level co-occurrence matrix can describe the coal feature exactly and recognize the coal and non-coal.