Segmentation of defects from radiography images by the histogram concavity threshold method

Abstract

A histogram concavity-based thresholding approach has been used for segmenting porosities, voids and inclusions from digitised radiography images. Studies on small defects in cylindrical tubes and flat plates show that histogram concavity-based thresholding approach yields better results compared to conventional automatic thresholding techniques like Maximum Entropy and Otsu methods, where heterogeneous background present in the image due to the geometry and large X-ray quantum and structural noise gives poor segmentation. The segmentation procedure is optimised by filtering the abrupt noises with low-pass median filtering, followed by grey-level global thresholding. The histogram concavity-based thresholds provided excellent segmentation of pores and voids present in Electrochemical Hydrogen Sensors (ECHS), cast plates used in refineries, micro-pores in tube-to-tubesheet (TTS) welds of steam generator of fast breeder reactor, tungsten inclusion in Tungsten Inert Gas (TIG) welds, crater crack and external undercut in welds. An accuracy of ± 1-2 pixel sizes (65-130 microns) is obtained for the estimation of defects sizes from the grey-level profiling.