Abstract
Based on photometric differential analysis, a new comprehensively-designed and appropriately-performed method was proposed for the pattern analysis of woven fabrics. In this paper, a specially-developed imaging system equipped with a four-side illumination module was established. Firstly, histogram equalization and adaptive wiener filtering for making the yarn profile more apparent were carried out followed by the gradient pyramid fusion of images captured under four illumination directions. Secondly, drawing support from adaptive mesh model, images captured under four illumination directions were divided into sub-images of each interlacing point on the basis of gray scale projection algorithm. The gradation of the convex portion in sub-images was adjusted. Adjusted region was marked as a highlight region to determine attribute category of the interlacing point. Finally, the weave pattern repetition image was generated. Experimental results indicated that almost 97.22% recognition accuracy of weave pattern could be achieved. This method eliminated mutual interference from different yarn directions.
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