Abstract: Facial expression recognition is the main factor in human communication that helps us to understand the intension of other emotions. This paper is going to relate human emotions such as anger, happiness, neutral, sad, surprise, disgust. In order to recognize facial expressions from the machines we employed some techniques called local binary pattern (LBP) for face recognition, the algorithm used here is local binary pattern histogram (LBPH), and for detection of face Haar-cascade classifier is used. With this work, the expression of the respective image will be reported, and it will also notify time taken for training an image. A small change in facial expressions signifies lighting, orientation and background. Here the LBP technique is intended only for the purpose of extracting features and Haar-cascade classifier is being utilized for the extracted features from LBP. The dataset is used for the purpose of testing and training of the images.

Keywords: Facial expression recognition, image processing, local binary pattern, Haar-cascade classifier, Feature extraction, Face detection.

| DOI: 10.17148/IARJSET.2022.9602