Experimental study on gray and texture features extraction of coal and gangue image under different illuminance

In order to study the response characteristics of coal and gangue under different illuminance,a coal-gangue image acquisition system with adjustable illuminance was designed,and some coal-gangue image acquisition experi-ments were carried out. A coal-gangue gray sub-image database was established,and the gray and texture features of the sub-images in the database were extracted. By defining the Normalized Feature D-value Index (NFDI) and train-ing the support vector machine (SVM) classifier,the experimental data were analyzed. The results show that coal and gangue exhibit some different gray and texture characteristics under the same illuminance,and these characteristics change with the change of illuminance. The recognition accuracies of SVM classifiers based on different characteristics are different. When the illuminance factor is taken into consideration,the recognition accuracy of SVM based on gray and texture features is improved. In addition,the SVM classifier based on the multiple features and illuminance fusion shows a good performance,and the recognition accuracy reaches 98. 39% .