Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28655
Title: Integrated digital system for yarn surface quality evaluation using computer vision and artificial intelligence
Authors: Li, SY
Feng, J
Xu, BG 
Tao, XM 
Keywords: Artificial neural network
Image processing
Intelligent system
Yarn evaluation
Issue Date: 2012
Source: Proceedings of the 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2012, 2012, v. 1, p. 472-476 How to cite?
Abstract: The evaluation method of yarn surface quality currently in use is mainly based on manual inspection. In order to resolve the inherent limitations of the human visual inspection, an intelligent evaluation system has been developed for the objective and automatic evaluation of yarn surface quality with computer vision and artificial intelligence. In this system, all yarn surface features are fully digitalized and quantitatively processed to ensure an objective evaluation of yarn surface appearance. This digital system integrates and controls the whole progress of yarn surface analysis, including the image acquisition, digital feature extraction, characteristic parameter computation and yarn quality classification, in one computer program with an interactive and friendly user interface. Besides yarn quality classification, multiple yarn surface characteristics, such as yarn diameter irregularities, yarn fault areas, foreign matters and fuzziness, can also be quantitatively obtained and visibly displayed.
Description: 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2012, Las Vegas, NV, 16-19 July 2012
URI: http://hdl.handle.net/10397/28655
ISBN: 9781601322258
Appears in Collections:Conference Paper

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