Facial Expression Recognition Based on Local Features and Monogenic Binary Coding
Abstract
Facial expression is a recognition technology for biological features, which is very significant and practical and has bright market prospects and fast development. In the study, monogenic binary coding algorithm was first considered to illustrate its operation process and good matching with local features through the analysis of monogenic signal theory and monogenic binary algorithm. Then, the results of facial expression recognition simulation experiment of monogenic based on classical facial expression database, Japanese Female Facial Expression (JAFFE) Database, and the results of traditional Local Binary Patterns-Sparse Representation-based Classification (LBP-SRC) residual fusion method were compared to illustrate the efficiency of monogenic binary coding algorithm in the aspect of facial recognition and provide a basis for the application of monogenic signal theory in facial expression.
DOI:
https://doi.org/10.31449/inf.v43i1.2716Downloads
Published
03/01/2019
How to Cite
Chen, Z. (2019). Facial Expression Recognition Based on Local Features and Monogenic Binary Coding. Informatica, 43(1). https://doi.org/10.31449/inf.v43i1.2716
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Section
Regular papers
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