Iris Recognition Scheme Based on Entropy and Convolutional Neural Network
DOI:
https://doi.org/10.46604/aiti.2024.13516Keywords:
iris, segmentation, morphology, entropy, CNNAbstract
This study presents an advanced iris image segmentation approach to overcome vibration and occlusion from the lashes. The proposed scheme removes the surrounding areas of the iris image to recover the region of interest (ROI) containing the iris images. The entropy function and mathematical morphology are employed as the foundation of the proposed scheme. Initially, the entropy function is applied to the binarization image. Subsequently, the ROI is cropped and extracted from the binary image using the dilation method. Furthermore, a convolutional neural network (CNN) is used in the recognition phase. The database of the Indian Institute of Technology Delhi (IIT Delhi) serves as a test. The results yield a high level of accuracy—up to 93% during segmentation. Using half of the dataset during the recognition phase results in an accuracy of 98.8%, while using the complete database produces an accuracy of 97.5%.
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