| Autor: |
Linyang Yan, Yu Shi, Minghua Wei, Yalin Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Alexandria Engineering Journal, Vol 63, Iss , Pp 307-320 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1110-0168 |
| DOI: |
10.1016/j.aej.2022.08.003 |
| Popis: |
In the field of Automatic Facial Expression Signal Recognition (AFESR) at video communication system, the fusing feature extraction is playing an extremely important role in recognition accuracy. This paper presents a new feature extraction method, Multi-Feature Fusing Local Directional Ternary Pattern (MFF-LDTP) which keeps more feature information and improvs the robustness under the uncontrollable and wild environment for AFESR. Firstly, the MFF-LDTP operator obtains the global feature of facial expression by Principal Components Analysis (PCA). Secondly, the MFF-LDTP enhances traditional Local Directional Ternary Pattern （LDTP）by using a “kirsch mask” to replace the Frei-Chen masks and selects the threshold for facial expression signal recognition. To effectively avoid generating invalid features, the MFF-LDTP extracts the local feature of eye and mouth which are significant regions by ELDTP. Thirdly, The MFF-LDTP final feature vector includes the linear connection of global and local features. The recognition rate for the extended JAFFE database is 96.5%. And the extended JAFFE includes captured sample images under an uncontrollable and wild environment. The experimental results show that the proposed MFF-LDTP achieved significant improvement and outperformed some state-of-the-art methods. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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