Identification of Mineral Grains in a Petrographic Thin Section Using Phi- and Max-Images

A new approach to identifying grains in a petrographic thin section is presented in this paper. The mineral grain boundaries are detected using two synthetic images, created by mapping the maximum birefringence color intensity (max-image) and the corresponding angular rotation at which it occurs (phi-image), instead of original images obtained by rotating the section between crossed polarizers. Edge detection and image segmentation operations are first applied on the phi- and max-images separately. The two segmented images resulting from edge detection are then combined to generate a new segmented image, which preserves edges with higher reliabilities and eliminates those with lower reliabilities in the two former segmented images. The identification rate is thereby greatly improved. The method has been implemented in C++ in the Linux environment. Two sets of images are used to test the method. Each set has 200 images corresponding to 200 rotation angles between 0 and 180°.