Identification of trash types in ginned cotton using neuro fuzzy techniques

Discusses the use of soft computing techniques such as neural networks and fuzzy logic based approaches in the identification of various types of trash (non-lint material/foreign matter) in ginned cotton. Lint is the cotton fiber; non-lint or foreign matter is everything other than lint. The effectiveness of a hybrid neuro-fuzzy structure, namely the adaptive-network-based fuzzy inference system to classify trash types is compared to other techniques. Shape descriptors like shape factor, extent, and solidity measures are used as features to distinguish trash types.