Saki pattern recognition in a woven fabrics using neuro-fuzzy system

Abstract

The importance of pattern recognition cannot be over emphasized as it cuts across many fields. Majority of the work on fabric pattern recognition focuses on determining the nature of the wefts and wrap in a given cloth. Others are more concerned with defect detection of hand-woven fabrics. However, there are limited studies on Saki Pattern recognition. Saki is atraditional Fulani hand-woven material worn as everyday cloth by the Fulani Clan of Westand Central Africa. This research is aimed at recognizing a Saki pattern in woven fabricsusing a Neuro-fuzzy system. A total of 1500 images from ten (10) different samples of Saki are collected and pre-processed to extract relevant features. Principal component analysis(PCA) is used for dimension reduction and the images are trained using Back-propagationalgorithm (BP) Neural Network using Matlab. Fuzzy inference rules are then used forclassification. The result obtained from the experiment showed that all the ten (10) Saki samples were predicted accurately with an average of 80% similarity. Thus, providing a lotof information on Saki, this may help in preserving the Fulani cultural heritage and advancethe Saki textile industry globally.

Keywords: Fuzzy inference, Image processing, Pattern recognition, Fulani wear

Vol.26 No.1 June 2019