“…(3) resolution of input image [19,[37][38][39][40][41]: e.g., a low resolution image cannot show fine defects in fabric; (4) alignment of input image [3,42,43]: e.g., misalignment in image acquisition induces false defect detection in template matching approach; (5) size [37,44], and shape [45][46][47] of defects: e.g., defect of small size or defect similar to a pattern shape increases difficulties in recognition; (6) speed or computation complexity of defect detection [37,48,49]: e.g., long learning delays may not be practical; (7) lighting [13]: e.g., improper illumination yields poor resolution and contrast; and (8) image acquisition techniques: e.g., most inspection methods use digital cameras to capture images. However, alternative approaches are also available, such as near-infrared (NIR) [50], X-ray, multispectral imaging and polarimetry, which may provide extra features in defect detection.…”