Biometric Image Processing Recognition in Retinal Eye Using Machine Learning Technique

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Abstract

Biometrics finds a lot of application in the modern day security aspects whether it may be in industrial sector, defense sector or in domestic sectors. Entry of a person into an organisation in the work environment plays a very important role as unauthorized persons if entered into a premises may create a flutter & inviable to some terrorist attacks. Hence, biometrics of an authorized person into the work environment plays a very important role. There are a large number of biometric methods for identification, viz., physiological & behavioural. Some of them are face, fingerprint, iris, voice, hand, thumb, ear, vein, gait, code, password, signature, pattern, palm print, etc. As there are a number of biometric methods for the automatic detection of human beings, retina scan is being considered as the biometric identity in the research work undertaken by us because of a large number of advantages over the other biometric identities. For biometric recognition of a person using retina scans, a number of methods exists in the literature. In this context, fractal dimension method is one of the method that could be used. Hence, the retinal recognition is performed in our proposed work for identifying the person by developing new approaches using Fractal Dimension methodologies. Hybrid algorithms are to be prepared & finally the developed codes are going to be run which are going to be performed in the Matlab environment, the simulation results are going to be observed and compared with the research work done by alternate scientists & engineers till now in order to build up the amazingness of the works done by us. This article gives the info about the exhaustive summary of the work carried out by us & that is going to be done along with the methodology that is going to be used for solving the desired objective and arrive at the outcome.

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Gururaj, J. P., & Ashok Kumar, T. A. (2020). Biometric Image Processing Recognition in Retinal Eye Using Machine Learning Technique. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 31, pp. 792–800). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-24643-3_93

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