Bones detection from chicken breast meat using a competitive hopfield neural network and fuzzy filtering

The contaminant detection process of a food product is an important stage of a modem food production factory. The automatic detection of bones in raw chicken breast meat is a major problem. This paper presents a fuzzy reasoning algorithm for post-processing the segmented images of dual-band X-ray images of raw chicken breast. The results show that bone detection rates are considerably improved over non-fuzzy or crisp methods without increasing the false negative rate. Further work is proposed and recommendations made for improving the