Real-time detection of weft knitted fabric defects

In order to detect the weft knitted fabric defects automatically,a real-time system and algorithm for the detection were developed in which the hardware part included image acquisition,signal processing and illumination device,while proograming was performed by Halcon software.The kinds of weft knitted fabric defects were defined as irregular shape and linear shape according to the characteristics of the defects.The cellular neural network was applied for detecting the defects with obvious gray level distribution and irregular shape.The line detection based on Radon transform was first proposed to identify the defects according to their linear shape,because the gray level distribution of the image and background of such defects are very similar.The experiments indicated that the algorithm could effectively detect defects like hole,dropped stitch,fly,float,course mark and miss tuck associated with weft knitted fabrics.