Research Article
Akram Qureshi · Ajay Saini
Journal
International Journal of Digital Applications and Contemporary Research (IJDACR)
ISSN
2319-4863
Volume / Issue
Vol.7 · Issue 10
Published
May 2019
Access
Open Access
Licence
CC BY-NC-SA 4.0
This paper presents the use of biometric identification through iris recognition, in specific environments that require a high level of security, such as penitentiaries. The image processing technique is utilized to process the human iris database images. It finds the centre coordinates along with the radius for the iris. Noise elimination around the iris image is also performed. The extracted features are the inputs for the random forest classifier which provides the output in the form of class for the identification of the person. In this paper, a hybrid approach of feature extraction based on different combination of Gabor wavelet and Harris Corner method is proposed. Random forest classifier is used for classification of extracted features. The simulation results are tested for the publicly available databases; CASIA iris image database, IIITD CLI iris image database, and achieve outperforming results for the iris matching. The hybrid feature extraction provides 98.9% of accuracy with proposed experimental setup.
Akram Qureshi, Ajay Saini (2019). Iris Recognition using Gabor Wavelet, Harris Corner and Random Forest Classifier. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.7, Issue 10. ISSN: 2319-4863.
Full references are available in the PDF version of this paper.
Download Full Paper (PDF) →Share This Paper
Call for Submissions
IJDACR accepts submissions on a rolling basis. Authors are advised to consult the preparation guidelines and scope documentation prior to submission.
Submissions are subject to editorial screening and peer review. Submission does not guarantee acceptance.