Metallurgical Analysis On Grey Cast Iron Based On Digital Image Processing

Grey cast iron was selected as the researched materials in this paper. According to the standard of quantitatively detecting, experiment selected enlarge multiple is 100×, 200×and 500×to capture metallographic image. This paper provided the study on microstructure image processing and analyzing methods based on digital image processing. The main achievements and conclusions are as follows:1. Aiming at the non-uniform phenomenon of microstructure image brightness, one method which based on the theory of shadow remedy was used to remedy it; the algorithms which combined wavelet transform and mean filtering was used to reduce the noise of image.2. Some segmentation methods, such as threshold method, FCM method, Genetic algorithm and wavelet transform, were used to segment the grey cast iron microstructure image, and this paper analyzed the segmentation results and performance of algorithm. In this foundation, an approach for grey cast iron image segmentation, called Genetic algorithm based on 2-D maximum between-cluster variance in wavelet domain, was presented. Segmentation result shows that the algorithm achieves good performance.3. Graphite quantity, ferrite quantity, pearlite quantity were calculated by area, graphite length was calculated by the distance of two pixel points, graphite form of grey cast iron was recognized by fractal theory, the span between pearlite flakes was calculated by the distance of two pixel points in this paper.4. A analyzing system of grey cast iron metallography was developed based on Matlab.