Methods of image processing for automatic grading of porosity defects in aeronautical alloy

Aiming at the disadvantage of manual grading of porosity in aeronautical alloy cast currently, a method of automatic grading by image processing and pattern recognition of computer to images got by X-ray radiography was put forward, and the methods of image processing and pattern recognition were mainly studied. According to the characteristics of gray distribution in typical porosity image, an algorithm of wavelet was taken to filter the disturbance of low frequency, which can remain the information of high frequency. Then segmentation was taken to pick up the porosity region and dimension characteristics of single porosity further, and macroscopic statistics and analysis was carried out. Neural network training was adopted by standard images from first level to eighth level, and finally the automatic grading of porosity was realized. The experimental results show that the method of image processing has good adaptability.