A coal-rock image feature extraction and recognition method
SUN Jiping
YANG Kun
Abstract：A coal-rock image feature extraction and recognition method based on binary cross-diagonal texture matrix was proposed.Binary cross-diagonal texture matrix of coal-rock image is extracted firstly.Then feature vector of coal-rock image is constructed by angular second moment energy,relevance,variance,inverse difference moment,entropy,sum entropy,difference entropy,sum average,contrast,inertia moment and information measurement of correlation,which are extracted from the binary crossdiagonal texture matrix.Finally,sparse representation is adopted to recognize coal-rock images.The experimental results show that the method can achieve better performance than image feature extraction and recognition method based on cross-diagonal texture matrix,whose average recognition rate can reach 94.38％,and improve real-time performance of coal-rock recognition with shorter feature extraction time of single image.
Keywords：coal-rock recognitioncoal-rock imagefeature extractionbinary cross-diagonal texture matrixsparse representation
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 1-5 )