Document Type : Original Research Paper
Authors
1 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
2 Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Abstract
Background and Objectives: The world we live in everyday, accompany with enormous numbers of minute variations which affect us and our surroundings in several aspects. These variations, so called micro-changes, are low in intensity and brief in duration which makes them almost invisible to naked eyes. Nonetheless, revealing them could open up a new wide range of applications from security, business, engineering, medical, and seismology to psychology.
Methods: In this paper, we adopted a novel autonomous approach comprising Partial Differential Equations (PDE) and Cubic Uniform Local Binary Pattern (Cubic-ULBP) to spot micro-changes. Cubic-ULBP extracts 15 planes containing robust features against noise and illumination variations. Afterwards, PDE pick out single plane out of 15 to reduce time consumption. Results: The proposed method is not only optimized to get the job done perfectly but also provides promising results comparing with most state-of-the-art methods. So that the accuracy is increased about 36% and 40% on the CASME and the CASME II databases, respectively.
Conclusion: The combination of the PDE and the Cubic-ULBP creates a strong and optimal method for detecting the apex frame and micro-movement. This method's performance is found to be promising when the training samples are scarce, too.
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Open Access
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Publisher
Shahid Rajaee Teacher Training University
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