The traditional production method of tufted carpets is manufactured by hand,and the efficiency is low and the quality is difficult to guarantee,which cannot meet the huge demand of the market.The digital manufacturing of tufted carpets can effectively improve production efficiency and quality,and bring more benefits to enterprises.Therefore,it is especially necessary to realize the digital manufacturing of tufted carpets.The tufting path generation technology of carpet machine is the key technology to realize the digital manufacturing of carpet.This paper has carried out related research on this technology,and its main research contents are as follows:(1)The overall design of the technical scheme of tufting path generation is studied.According to the requirement of bitmap format input and vector tufting path output,the overall design scheme defines six key technologies,and establishes a software architecture which is easy to maintain and expand later.(2)An algorithm for automatically extracting the main constituent colors from the carpet image was studied.There are a limited variety of yarn colors during carpet tufting,But there are many kinds of pixel colors in a carpet image.Through the color quantization algorithm and the color clustering algorithm,the pixel color types in the carpet image are effectively reduced,and the main constituent colors of the image are automatically extracted.(3)The contour extraction and vectorization algorithms are studied around the image contour.The edge of the patch image is extracted by the edge detection algorithm,and the edge pixel is tracked by the chain code tracking algorithm.Finally,based on the Bezier parameter equation,the edge pixels are curve-fitted,and the contour is vectorized.It can be applied to carpets of any size by zooming the tufted outline..(4)The path filling algorithm of horizontal filling is studied.Based on the concept of monotone chain and scan line algorithm,the clustering path generation algorithm is studied,and a relatively continuous horizontal filling algorithm is obtained. |