Segmentation and Extraction for the Diamond Grain Image Based on the Gauss-polymerized Enhancement

Abstract

To solve the problem of many background noises in image segmentation of diamond grains under the complicated texture background, an image segmentation and extraction method for diamond grains based on the Gauss-polymerized enhancement was proposed in this work. Firstly, the original diamond grain image was pre-processed by the method of histogram equalization in order to enhance the overall contrast effect of the image. Secondly, the image was further processed by the method of Gauss-polymerized enhancement through setting proper Gauss filter parameters, which purpose is to enhance the boundary definition between the grain and the matrix, and reduce the complex background noises. On this basis, the morphological dilation was used to eliminate the non-interested regions of the complex background noises, and obtain the segmentation region of the interested target grain. Finally, the diamond grain can be extracted from the grain image based on the segmented region of the target grain through the operation of image multiplication. The results show that the proposed method can effectively reduce the influence of the complex texture background on the segmentation and extraction of the target grain. The extracted image of the target grain can be further used to analyse the grain size characteristics and grain wear pattern identification in a higher level.