Saliency-based color image segmentation in foreign fiber detection

Abstract

It is difficult to separate foreign fiber objects from the background in a live image captured by an automated visual inspection system for foreign fiber detection due to the inhomogeneous background brightness and various types of foreign fibers in different colors and shapes. This paper presents a saliency-based color image segmentation method aiming at foreign fiber detection. The RGB color image captured in real-time was firstly separated into R, G and B color channels. Then the red, green and blue color features were calculated respectively from the corresponding R, G and B channels. Afterwards, three saliency maps were obtained from these three color features and then fused together. The fused saliency map was segmented to get the color foreign fiber objects. Those foreign fiber objects in dark black or bright white were also segmented out using a threshold method from the brightness saliency map. Finally, all foreign fiber objects obtained were fused together to obtain the final objects. The results indicate that the proposed method can segment out color foreign fiber objects as well as gray foreign fiber objects in dark black or bright white.