With the growth of the global economy and the widespread use of aluminum profiles, the global consumption of aluminum castings has been increasing year by year. Due to the different applications, there are a variety of aluminum castings, they have different shapes, structures, colors, textures and so on. As an important aspect of the image processing application, this study analyzes the features of aluminum castings, extracts the texture features of the image by using the gray level co-occurrence matrix and Gabor wavelet transform, respectively, and compares them with the SVM classification algorithm of SVM feature classification, test recognition accuracy, experimental results were compared for the classification of aluminum castings obtained Gabor wavelet transform using both the recognition accuracy or recognition of time on the results are the best.