Digital coal petrography analysis system introduced in this paper is an integrated system that has three main functions: image acquisition

composition recognition and analysis of quality of coal. The key techniques of this system are auto focus

auto exposure

texture analysis

pattern recognition and analysis of coal petrography. A price function is used to implement auto focus; it is the sum of the gray grads of all pixels in three small windows in the same image

and is determined by the Z Axis of the lens of microscope; the need is met when the function takes extremum value. Auto exposure is achieved by using a test of exposing in a very short time; the correct exposure time can be calculated with the gray histogram of the image obtained in the testing exposure. Studied the features of the composition of coal

the methods of classifying by gray threshold and principal component analysis (PCA) are adopted to implement texture analysis and pattern recognition. Moreover

some other techniques like estimating of parameters by use of artificial neural network are used in this system. The experimental results show that all these methods can greatly improve the efficiency and veracity of analysis of coal petrography. Both the speed and the precision of coal petrography analysis are satisfactory. The system is used in the industrial research successfully.