Segmentation of Thermographic Sequences in Frequency Modulated Thermal Wave Imaging for NDE of GFRP

Image processing techniques have become highly essential to improve the data usefulness of the raw images obtained for infrared non-destructive evaluation (NDE). The identification of defective regions from a thermogram has been a common problem in the field of NDE. Image segmentation is one of the promising approaches to identify defective regions from thermogram. In the present work, segmentation approach based on clustering is employed. In this image patterns are organized into clusters or groups considering the relationship among these. The method involves finding the centroids of the regions and formation of clusters around each centroid. Thresholding is applied to improve accuracy in formation of clusters. Double thresholding method is adapted to retrieve the shape of defect and to improve the possible diagnosis capabilities of system for NDE applications. The proposed method is investigated with frequency modulated thermal wave imaging (FMTWI) over glass fiber reinforced polymers (GFRP). The GFRP sample consists of square shaped Teflon inserts of different dimensions placed at various depths. A comparative study of the proposed novel segmentation scheme and existing segmentation methods is conducted.