Defect detection in textile materials based on aspects of the HVS

The problem we address in this paper is that of detecting flaws in woven textile fabrics. This task is currently performed by human inspectors with a maximum detection rate of only about 80%. An Automated Visual Inspection System (AVIS) is potentially a more reliable, objective, time and cost effective solution. Using computer vision it detects irregularities in homogeneously structured images of textile fabrics. However, its successful performance is largely dependent of the choice of an accurate and robust texture analysis algorithm. The technique of blob detection described in this paper is representative of a structural texture analysis approach and it accounts for aspects of the human visual system (HVS) in detecting large varieties of textile flaws. Measures of texture discrimination based on psychophysical experiments are used to indicate the levels of perceivable differences in blob attributes indicating the presence of defects. Defects are detected by observing a threshold of acceptable differences in the properties of blobs based on human perception.