Enhance iris segmentation method for person recognition based on image processing techniques

The limitation of traditional iris recognition systems to process images captured in unconstraint environments is a breakthrough. Automatic has face unpredictable variations real-world applications. For example, the most challenging problems are related severe noise effects that inherent these unconstrained systems, varying illumination, obstruction upper or lower eyelids, eyelash overlap with region, specular highlights on pupils which come from spot light during image, and decentralization image caused by person’s gaze. Iris segmentation one important processes recognition. Due different types eye result may be erroneous. To solve this problem, paper develops an efficient algorithm using processing techniques. Firstly, outer boundary problem solved. Then pupil detected. Testes done Chinese Academy Sciences’ Institute Automation (CASIA) database. Experimental results indicate proposed effective terms reduction time processing. accuracy for both datasets (CASIA-V1 V4) 100% 99.16 respectively.