• P.Chandansree
• Prof.S.Varadarajan

The paper proposes a hybrid approach for iris detection and recognition using Fuzzy C Means (FCM), Gray-Level Co-occurrence Matrix (GLCM), and Convolutional Neural Networks (CNN) in MATLAB 2013a version. The proposed method consists of several steps, including preprocessing, segmentation using FCM, feature extraction using GLCM, and classification using a CNN model. The segmentation using FCM and feature extraction using GLCM enable the extraction of more discriminative features for better classification performance. The CNN model is trained on the extracted features and achieves high accuracy in iris recognition. The proposed method outperforms existing methods in terms of both accuracy and computational efficiency. The approach presented in this paper is promising and could be applied in various applications such as security systems, access control, and healthcare.

Iris , CNN, FCM,GLCM etc.,

"IRIS DETECTION AND RECOGNITION BY IMAGE SEGMENTATION AND CONVOLUTION NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.d723-d729, March-2023, Available :http://www.jetir.org/papers/JETIR2303391.pdf

"IRIS DETECTION AND RECOGNITION BY IMAGE SEGMENTATION AND CONVOLUTION NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppd723-d729, March-2023, Available at : http://www.jetir.org/papers/JETIR2303391.pdf