The image synergetic classification of cancer cells based on prototype modify with rough set methods
Gang Zou, Shuhua Teng, Shilin Zhou, Jixiang Sun, Senlin Chen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
The essence of Rough set theory is a mathematic tool describing imperfection and uncertainty, can effectively analyze and deal with those imprecise, inconsistent, incomplete or other imperfect information so as to find out the implied knowledge. The synergetic pattern recognition is a new way of pattern recognition with many excellent features such as noise resistance, deformity resistance, and better robustness. The selection of prototype patterns is very important to pattern recognition of synergetic approach. The main research now is focused on prototype modify from eigenvalue instead of image pixel. Division matrix of rough set can get the best reduce result, and Furthermore dynamic rough set method is applied and optimal non-linear features are got as prototype patterns. Experiment result on cervical squamous intraepithelial cell images shows that the new algorithm can effectively search the optimal prototype patterns, the synergetic recognition method proposed in this paper is more available, and excellent, correct and fast recognition result has been achieved.