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Iris Recognition Supported best Gabor Filters and Deep learning CNN Options | IEEE Conference Publication | IEEE Xplore

Iris Recognition Supported best Gabor Filters and Deep learning CNN Options


Abstract:

Proposed Method we have created iris recognition using neural network. Purpose of iris is for rareness and authentication. Vision of smart city leads to strong security s...Show More

Abstract:

Proposed Method we have created iris recognition using neural network. Purpose of iris is for rareness and authentication. Vision of smart city leads to strong security system to prevent country from crime. Conquest, accuracy and popularity of Machine Learning has been a lot of curiosity in applying structures scholarly by NN on image recognition [6]. Neural Network here because Neural Network is a basically Self Learning computationally intelligent System. Once we Make it People Can use it easily it also reduces the human interaction. In this paper we utilized Gabor filters for creating feature vector from iris features. Here comparison is with trained neural network. In this work authors are using supervised neural network, which is first trained and with different inputs of different iris feature vectors and then recognition is done.Here we have tried to prove usefulness of features extracted from neural network and Gabor filter for iris recognition. This method have used CASIA iris databases, here we got result up to rate of 99.999%, which overtakes the other related work. we can also apply the same method for other Iris images also.
Date of Conference: 13-15 February 2020
Date Added to IEEE Xplore: 28 May 2020
ISBN Information:
Conference Location: Pune, India

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