Theses and Dissertations @ UNI


Open Access Dissertation


Industries look toward computer vision as a means to automate materials handling. To make this choice more appealing, useful and feasible vision applications must be developed. However, illuminance variation in the factory environment can undermine the capability and applicability of vision-based control systems. The purposes of this study were (a) to design and develop a vision-based robot material sorting system, (b) to determine the optimal settings for this system under fluorescent and incandescent lighting for two different color parts on a moving conveyor, and (c) to determine the sorting performance of this system under each light source. The main components of this experimental system consisted of: (a) a robot system with a slide base and a speed controlled conveyor, (b) a ROBOTVISION plus vision system, (c) an incandescent lamp light intensity controller, and (d) two PCs. By integrating these components, color sorting applications were developed. This study explored two sorting methods. Method A used the difference in object descriptors to separate the dominos. This method worked in a limited range of illuminance and identification tolerance for both light sources. Method B used the difference in the observed "saturation" response of the charge coupled device camera to separate the dominos. This method worked in a wide range of illumination with no stipulation on identification tolerances for both light sources.

Year of Submission



Department of Industrial Technology

First Advisor

Ahmed Elsawy, Advisor

Date Original


Object Description

1 PDF file (x, 126 pages)



File Format