Coal-rock interface identification based on image multi-wavelet transformatio

Abstract

In view of problems of poor universality and low reliability in existing identification method of coal-rock interface, an identification method of coal-rock interface based on image multi-wavelet transformation was proposed. Firstly, coal-rock image is transformed by multi-wavelet. Then standard deviation under fixed window size with multi-wavelet coefficients of different frequency bands is extracted as texture measure and normalization multi-band feature vector is formed. Finally, texture feature is identified by naive Bayes classifier. The experimental results show that identification rate can achieve 96.14% when window size is 9 and feature vector constructed by frequency bands 5-16 for image of resolution 128×128.

Keywords

• coal-rock interface identification
• multi-wavelet
• multi-band feature
• naive bayes classifier