Abstract: Deduplication has been widely used in backup systems and archive systems to improve storage utilization effectively. However, the traditional deduplication technology can only eliminate exactly the same images, but it is unavailable to duplicate images, which have the same visual perceptions but different codes. To address the above problem, we designed and developed a back propagation based Artificial Neural Network (ANN) classifier, which is efficient in terms of learning time, ROC and computational efficiency during testing/prediction/classification phase. In addition, with a large amount of data and a careful designing of architecture, we can define a better feature selection from CBFD (Complex Binary Feature Descriptor) thereby ensuring higher accuracy.
Keywords: Facial Recognition System, Complex Binary Feature Descriptor, Artificial Neural Network (ANN), Digital Image Processing (DIP).
Title: Image Deduplication in Face Recognition using Back Propagation Neural Network (BPNN)
Author: Jiten Kumar, Inderdeep Kaur
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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