Details

Autor(en) / Beteiligte

• Khuzani, Abolfazl Zargari
• Mashhadi, Najmeh
• Heidari, Morteza
• Khaledyan, Donya

Titel

An approach to human iris recognition using quantitative analysis of image features and machine learning

Ist Teil von

• 2020 IEEE Global Humanitarian Technology Conference (GHTC), 2020, p.1-6

Ort / Verlag

IEEE

Erscheinungsjahr

2020

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• The Iris pattern is a unique biological feature for each individual, making it a valuable and powerful tool for human identification. In this paper, an efficient framework for iris recognition is proposed in four steps. (1) Iris segmentation (using a relative total variation combined with Coarse Iris Localization), (2) feature extraction (using Shape & density, FFT, GLCM, GLDM, and Wavelet), (3) feature reduction (employing Kernel-PCA) and (4) classification (applying multi-layer neural network) to classify 2000 iris images of CASIA-Iris-Interval dataset obtained from 200 volunteers. The results confirm that the proposed scheme can provide a reliable prediction with an accuracy of up to 99.64%.