Facial expression recognition for wild dataset using LBP features and Random Forest Classifier

Shubhangi Patil-Kashid; Y.M. Patil; Anandrao S. Kashid

doi:10.62110/sciencein.jist.2024.v12.817

Authors

Shubhangi Patil-Kashid N.K. Orchid College of Engineering and Technology, Solapur https://orcid.org/0000-0002-6993-5686
Y.M. Patil KIT’s College of Engineering, Kolhapur
Anandrao S. Kashid N.K. Orchid College of Engineering and Technology, Solapur

DOI:

https://doi.org/10.62110/sciencein.jist.2024.v12.817

Keywords:

Facial Expression Recognition, Random Forest classifier, wild dataset, pre-processing, feature extraction

Abstract

Face expressions play major in communication. If machines are facilitated with expression recognition then humans can interact with machines same as humans. A lot of research is carried out in last forty years to find best algorithm for face expression recognition. Good recognition accuracy is achieved for posed images captured in controlled scenario. In this research paper a novel method is proposed for real time images. All the images in dataset are preprocessed before feature extraction. Texture information of images is obtained by using LBP features and random forest classifier is applied on the features extracted. The algorithm is tested by using four datasets and good recognition accuracy is achieved with real time dataset also.

URN:NBN:sciencein.jist.2024.v12.817

Downloads

Download data is not yet available.

Author Biographies

Shubhangi Patil-Kashid, N.K. Orchid College of Engineering and Technology, Solapur

Department of Electronics and Telecommunication Engineering
Y.M. Patil, KIT’s College of Engineering, Kolhapur

Department of Electronics & Telecommunication Engineering
Anandrao S. Kashid, N.K. Orchid College of Engineering and Technology, Solapur

Department of Mechanical Engineering