Automatic online recognition of foreign fibers from cotton using machine learning

Abstract

As we all know that food, clothes and house are the important things. To get the best clothes purified cotton need to remove foreign fibers from being mixed with cotton. It is a tremendous and most challenging task to accurately classify foreign fibers from cotton. This article proposes a proficient recognition and classification system to accurately recognize foreign fibers mixed with cotton. In machine learning, the kernel extreme learning machine is the main component. It is an efficient classifier based on the two-step grid search strategy which collect a active search with a fine search and is adopted to train an optimal KELM recognition model in it. To find out the accurate result, the final model is compared with valid data set using tenfold cross-validation analysis. In this paper an experimental results show that the proposed recognition system can be achieve classification accuracy as high as 93.57 percent which is greater than the other two state-of-the-art systems.