Iris recognition is a method of biometric authentication that uses pattern-recognition techniques based on high-resolution images of the irises of an individual's eyes. Iris recognition efficacy is rarely impeded by glasses or contact lenses. Iris technology has the smallest outlier of all biometric technologies and in this regard as the most reliable and accurate biometric identification system available. An approach for accurate Biometric Recognition and identification of Human Iris Patterns using Competitive Neural Network (LVQ) and Cascade forward backpropagation is designed using Matlab. The improved methodology suggested has resulted in the reduction of the space requirement as well as time complexity with no loss in accuracy. Simulation results of iris recognition performed by applying Competitive Neural Network (LVQ) and Cascade forward back propagation are shown in the video demo. The data set image is on the web at

Reference Paper-1: IRIS Recognition Using Neural Network

Author’s Name: Leila Fallah Araghi, Hamed Shahhosseini, and Farbod Setoudeh

Source: IMECS


Reference Paper-2: Improved Biometric Recognition and Identification of Human Iris Patterns Using Neural Networks

Author’s Name: M. Gopikrishnan, and T. Santhanam

Source: Journal of Theoretical and Applied Information Technology


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SIMULATION VIDEO DEMO