A New Pseudo-color Transform for Fibre Masses Inspection of Industrial Images
用于工业异纤分检的一种伪彩色方法(英文)

In this paper, we propose a novel pseudo-color approach which can effectively mark all different particulars while it has the ability to divide foreign pieces with indiscernible brightness in fibre masses. Hence, it yields highly separate color images for this kind of industrial images. Our approach aims at constructing an adaptive fuzzy rule based on a feature space of gradients, gray values, local entropies, and local features from scalable morphological filters. Due to the fact that the method is based on a full contextual information, it can handle small changes in images more adaptively than classical pseudo-color methods. And it is perfectly suitable to distinguish impurities mixed in fibre masses, as tested in a simulating cotton inspection system and demonstrated by several cotton sample images.