Abstract:

This paper proposed a new defect detection method for mini-jacquard fabric based on visual saliency. This method firstly analyzed the characteristic of the mini-jacquard and proposed to apply fast Fourier transform and mathematical morphological filter on the original image to keep down the saliency of the normal area, pop out the saliency of the defect area and obtain the global saliency map; and then, the local saliency map was obtained by using the graph-based visual saliency model; after that, the saliency map could be generated by combine the global and local saliency map; and finally, a maximum entropy method was implemented on the saliency map to separate the defected area. Experimental results show that the proposed method can effectively detect multiple kinds of defects of barre, hole, broken end, knots and netting, and the average success rate is 93.5%. It is an effective defect detection method.

Key words: mini-jacquard fabric, defect detection, visual saliency, maximum entropy method