A Vision Based Bio-Cell Recognition for Biomanipulation with Multiple Views

Manipulation of the nano/micro scale object has been a key technology in biology as the sizes of DNA, chromosome, nucleus, cell and embryo are within such order. For instance, for embryo cell manipulation, the cell injection is performed manually. The operator often spends over a year to carry out a cell manipulation project. Since the typical success rate of such operation is extremely low, automation of such biological cell manipulation has been asked. As the operator spends most of his time in finding the position of cell in the Petri dish and in injecting bio-material to the cell from the best orientation. In this paper, we propose a new strategy and a vision system, by which one can find, recognize and track nucleus, polar body, and zona pellucida of the embryo cell for automatic biomanipulation. The deformable template matching algorithm has been used in recognizing the nucleus and polar body of each cell. Result suggests that it outperforms the conventional methods.