Identify a person from Iris Pattern using GLCM features and Machine Learning Techniques

International Journal of Computer Science and Engineering
© 2020 by SSRG - IJCSE Journal
Volume 7 Issue 9
Year of Publication : 2020
Authors : Deepak Singh, Mr. Mohan Rao Mamdikar

How to Cite?

Deepak Singh, Mr. Mohan Rao Mamdikar, "Identify a person from Iris Pattern using GLCM features and Machine Learning Techniques," SSRG International Journal of Computer Science and Engineering , vol. 7,  no. 9, pp. 25-29, 2020. Crossref,


In today's era, when we see a pandemic like a corona, we can understand the need for nonimpact biometric feature matching techniques. Iris recognition is one of the accurate biometric features that can be used to identify a person. Iris recognition, as an emerging biometric recognition approach, is becoming an active topic in both research and practical applications; Iris recognition is recognizing an individual by analyzing the apparent pattern of his or her iris. A typical iris recognition system includes iris imaging, iris detection, feature extraction, and recognition. Here, we are proposing a straightforward approach for segmenting the iris patterns using a global thresholding technique. After this step, we get the iris' pupil, which is subtracted from the original image to urge the iris part. Then GLCM features are extracted from the iris, and machine learning techniques will do training and testing. We plan to perform Experiments using iris images obtained from the CASIA database. The general accuracy we get is promising, with near about 99% on using a support vector machine classifier.


Iris detection, machine learning techniques, CASIA dataset, GLCM features.


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