The Performance Evaluation of Classic ICA Algorithms for Blind Separation of Fabric Defects

The Performance Evaluation of Classic ICA Algorithms for Blind Separation of Fabric Defects

Year:    2014

Journal of Fiber Bioengineering and Informatics, Vol. 7 (2014), Iss. 3 : pp. 377–386

Abstract

Independent Component Analysis (ICA) is a blind source separation technique that has been broadly used in signal and image separation. In order to verify the feasibility of ICA algorithms which will be used for the detection of fabric defect, four kinds of classic ICA algorithms have been chosen and compared in terms of their algorithm performances. The results of simulation experiments show that the separation performances of these algorithms are different and FastICA algorithm has the best separation performance than others.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.3993/jfbi09201407

Journal of Fiber Bioengineering and Informatics, Vol. 7 (2014), Iss. 3 : pp. 377–386

Published online:    2014-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    10

Keywords:    ICA Algorithm