Abstract: To inspect turbine blade automatically, with a realtime radiographic system based on X-ray flat panel detector, computerized defect extraction techniques are studied on the basis of characteristics of turbine blade’s digital radiographic images. At first, in the light of a variety of gray-level in a turbine blade’s digital radiographic image, it is divided into six subareas. An adaptive median filter is used to smooth defects in each subarea. Then, the filtered image is subtracted from the raw image and a difference image with flat background and outstanding defects is obtained. After that, thresholding is applied to the difference image and defects in the turbine blade became obvious. Later on, a morphological opening is used to realize noise reduction. In order to ensure the accuracy of defects, a region growing method is adopted to reconstruct the defects. Finally, the feature data of defects are extracted. The comparison between computerized feature extraction results and human interpretation results indicated that the method mentioned above is effective and efficient, which laid a good foundation for automatic inspection of turbine-blade with X-ray.

Key words: Defect extraction, Image processing, Non-destructive testing, Real-time radiography, Self-adaptive median filtering