Iris Recognition Based Machine Learning

We Presentation algorithms for iris detection, feature extraction and feature selection, and iris model matching. To part the internal boundary from a nonideal iris, we apply a level set based sobel algorithm for edge detection, and to detect the outer boundary, we using decision tree is to extract the textural features. To speed up the process and to rein the classification error and segmentation, we apply a approach called the support vector machines (SVMs). The parameter values of SVM are also optimum in order to better the throughout generalization performance. The validation and identification performance of the proposed plan is verification using the CASIA datasets.

کلیدواژه ها:

Iris Recognition ، Machine Learning ، Decision Tree ، Support Vector Machines