2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 1 , Issue 1 , PP: 22-31, 2020 | Cite this article as | XML | Html | PDF | Full Length Article
Hardik Agarwal 1 * , Kanika Somani 2 , Shivangi Sharma 3 , Prerna Arora 4 , P. Singh Lamba 5 , Gopal Chaudhary 6
In this paper, unique features of the segmented image samples are extracted by using two major feature extraction techniques: Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). After this, these features are fused to get more precise and productive outcomes. The average accuracy of the three distinct datasets that were generated using the LBP and HOG features are determined. To calculate the accuracy of the three distinct models, classification techniques like KNN and SVM, are adopted.
Palm Print Recognition , Region of Interest , Local Binary Pattern , Histogram of Oriented Gradients.
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