An Iris Image Synthesis Method Based on PCA and Super-Resolution

It is very important for the performance evaluation of iris recognition algorithms to construct very large iris databases. However, limited by the real conditions, there are no very large common iris databases now. In this paper, an iris image synthesis method based on Principal Component Analysis (PCA) and super-resolution is proposed. The iris recognition algorithm based on PCA is first introduced and then, iris image synthesis method is presented. The synthesis method first constructs coarse iris images with the given coefficients. Then, synthesized iris images are enhanced using super-resolution. Through controlling the coefficients, we can create many iris images with specified classes. Extensive experiments show that the synthesized iris images have satisfactory cluster and the synthesized iris databases can be very large.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Jiali Cui, JunZhou Huang, Tieniu Tan, Yunhong Wang, Zhenan Sun
• Keywords: Coarse Iris Images, Computer Vision, ICPR 2004, Iris Image Synthesis, Large Iris Databases