Iris Identification Based on SVM-CNN Method
DOI:
https://doi.org/10.31642/JoKMC/2018/110209Keywords:
Recognition, Biometric, SVM, CNN, Identification, SegmentationAbstract
A person is automatically recognized in a biometric system by analyzing their distinct traits. Most people agree that iris recognition is the most accurate and dependable biometric identification method currently in use. The goal is to accurately and efficiently identify a person in real time by analyzing the sporadic patterns seen in the iris if an eye from some distance, by extracting strong features using deep learning technique. The extracting of significant features is important step that effect the overall accuracy of iris recognition system. In order to extract the iris characteristics, this research suggests a robust convolution neural network (CNN) structure. Then, an identity of the person is determine based on extracted features from his iris to support vector machine (SVM). The proposed system is examined on CASIA V. (1). Several parameters such as accuracy, precision, recall, and F-score are computed to evaluate the performance of the proposed system. The obtained result of the accuracy is about (99%). The proposed system results are compared with several previous methods and prove its effectiveness. A contemporary approach and the suggested method are contrasted and use deep learning for features extraction and the results depict our method outperforms other methods.
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