Intelligent worm sorting using robot vision

In this paper, the application issues of vision sensing techniques to analysing the body postures of worms are discussed. The worm targeted here is the nematode C. elegans (short for Caenorhabditis elegans), which is widely used for pursuing research in developmental biology and neurology. The image of C. elegans is firstly segmented based on pixel grey-values, and the extracted worm region is skeletonized. The worm body shape is then modelled with a chain of multiple links. As the link connection is in the same structure of a robot manipulator, a variety of analysis techniques developed in robotics can be readily employed in the automatic analysis of worm images. (C) 2012 The Authors. Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Centre of Humanoid Robots and Bio-Sensor (HuRoBs), Faculty of Mechanical Engineering, Universiti Teknologi MARA.