Applying Partial Differential Equations on Cubic Uniform Local Binary Pattern to Reveal Micro-Changes

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.