  The global market for textile industry is highly competitive nowadays.
Quality control in production process in textile industry has been a key factor
for retaining existence in such competitive market. Automated textile
inspection systems are very useful in this respect, because manual inspection
is time consuming and not accurate enough. Hence, automated textile inspection
systems have been drawing plenty of attention of the researchers of different
countries in order to replace manual inspection. Defect detection and defect
classification are the two major problems that are posed by the research of
automated textile inspection systems. In this paper, we perform an extensive
investigation on the applicability of genetic algorithm (GA) in the context of
textile defect classification using neural network (NN). We observe the effect
of tuning different network parameters and explain the reasons. We empirically
find a suitable NN model in the context of textile defect classification. We
compare the performance of this model with that of the classification models
implemented by others.
