Texture based feature extraction using symbol patterns for facial expression recognition.
Cogn Neurodyn
; 18(2): 317-335, 2024 Apr.
Article
en En
| MEDLINE
| ID: mdl-38699622
ABSTRACT
Facial expressions can convey the internal emotions of a person within a certain scenario and play a major role in the social interaction of human beings. In automatic Facial Expression Recognition (FER) systems, the method applied for feature extraction plays a major role in determining the performance of a system. In this regard, by drawing inspiration from the Swastik symbol, three texture based feature descriptors named Symbol Patterns (SP1, SP2 and SP3) have been proposed for facial feature extraction. SP1 generates one pattern value by comparing eight pixels within a 3×3 neighborhood, whereas, SP2 and SP3 generates two pattern values each by comparing twelve and sixteen pixels within a 5×5 neighborhood respectively. In this work, the proposed Symbol Patterns (SP) have been evaluated with natural, fibonacci, odd, prime, squares and binary weights for determining the optimal recognition accuracy. The proposed SP methods have been tested on MUG, TFEID, CK+, KDEF, FER2013 and FERG datasets and the results from the experimental analysis demonstrated an improvement in the recognition accuracy when compared to the existing FER methods.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Cogn Neurodyn
Año:
2024
Tipo del documento:
Article
País de afiliación:
India
Pais de publicación:
Países Bajos