A laser imaging method for machine vision detection of white contaminants in cotton

Abstract

The existing machine vision systems cannot efficiently detect white contaminants in cotton under the illumination of visible lights, because their color is the same or very close. To solve the problem, this article proposes an imaging method based on line lasers. Under the illumination of a line laser, the white contaminants and cotton showed the differences in the optical characteristic of their surface. Then, according to the features of the intensity of their reflected lights or the distribution of the fluff around their surfaces in the images, an example algorithm for identification of white contaminants from cotton was suggested. The experimental results indicated that, using our method, the mean successful detection rate of the typical white contaminants in cotton was over 87%.