A rock structure recognition system using FMI images

Formation Micro Imager (FMI) can directly reflect changes of wall stratum and rock structures. It is also an important method to divide stratum and identify lithology. However, people usually deal with FMI images manually, which is extremely inefficient and may incur heavy burdens in practice. In this paper, with characteristics of rock structures from FMI images, we develop an efficient and intelligent rock structure recognition system by engaging image processing and pattern recognition technologies. First, we choose the most effective color and shape features for rock images. Then, the corresponding single classifier is designed to recognize the FMI images. Finally, all these classifiers are combined to construct the recognition system. Experimental results show that our system is able to achieve promising performance and significantly reduce the complexity and difficulty of the rock structure recognition task. © 2009 Springer-Verlag Berlin Heidelberg.

Duke Scholars

Author Kaizhu Huang DKU Faculty