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The program uses HOG and LBP features to detect human in images. First, use the HOG feature only to detect humans. Next, combine the HOG feature with the LBP feature to form an augmented feature (HOG-LBP) to detect human. A Two-Layer Perceptron (feedforward neural network) will be used to classify the input feature vector into human or no-human.
A two-class fingerprint spoof detector that uses Local Binary Patterns (LBP) features along with Support Vector Machines (SVM) to distinguish live fingerprints images from spoof samples.