Research Article
Jahnvi Thahirani · Rohitashva Jajoo
Journal
International Journal of Digital Applications and Contemporary Research (IJDACR)
ISSN
2319-4863
Volume / Issue
Vol.7 · Issue 1
Published
August 2018
Access
Open Access
Licence
CC BY-NC-SA 4.0
The identification of individuals by their palmprints, considered as a new member of the family of biometric modalities, has become a very active area of research in recent years. The work done so far has been based on palmprints image representation techniques for better classification. This paper is divided into two phases, training phase and testing phase. In training phase there are three sub processes; pre-processing, feature extraction and dimensionality reduction. Pre-processing is done with the help of image resizing and RGB to Gray conversion. For feature extraction, we have used Gabor wavelet and wavelet moments. Principal Component analysis (PCA) is used for dimensionality reduction. The extracted features are then stored in database. In the testing phase the same process is done up to the PCA and then the similarity measure with database is done. Random Forest Classifier is used for similarity measure. The MATLAB image processing tool box is used to implement proposed Palmprint recognition system.
Jahnvi Thahirani, Rohitashva Jajoo (2018). Palmprint Recognition using Hybrid Features with Gabor Wavelet, Wavelet Moments and Random Forest Classifier. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.7, Issue 1. 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.