Extraction of Face Texture Features Based on Histograms of Oriented Gradients (HOG)
DOI:
https://doi.org/10.26438/ijcse/v6i3.168172Keywords:
Biometrics, Face Recognition, Histogram of Oriented Gradients, Multimodal Biometrics, VerificationAbstract
This research paper is designed on a unimodal biometric system. This system is based on Face recognition. The proposed modal consists of two major processes, the enrollment and the recognition. The enrollment is used for acquiring the template features which are called as the training features. The recognition means the involvement of the method which identifies the feature vectors from the template features to which that specific class belongs. This process is called as the testing and accuracy is obtained from this process. The Histograms of Oriented Gradients (HOG) are used for extracting the face features. This technique is applied for identification of a person on KVKRG face database. In this experiment total 200 images were used. KVKR Face database is developed under UGC-SAP Phase I (which is the researchers own major contribution) having 10 poses of each subject. The highest recognition rate is obtained by Ensemble (Subspace Discriminate) that is 98.8% and Linear Discriminant that is 100%. The experimental result has shown that biometrics system record an improvement in the overall system performance. Its results are quick and accurate.
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