Extraction of Eye and Mouth Features for Drowsiness Face Detection Using Neural Network

Extraction of Eye and Mouth Features for Drowsiness Face Detection Using Neural Network

Elis Fitrianingsih, Endang Setyati, Luqman Zaman


Facial feature extraction is the process of searching for features of facial components such as eyes, nose, mouth, and others from the human face image. Facial feature extraction is essential for initializing processing techniques such as face tracking, recognition of facial expressions or face shape recognition. Among all facial features, eye area detection is important, because of the detection and localization of the eye, the location of all other facial features can be identified. In this paper, we describe automated algorithms for feature extraction of eyes and mouth. Data in the form of video, from the video is then converted into a sequence of images / images through frame extraction. From the sequence of images, feature extraction is based on the morphology of the eyes and mouth using the Neural Network Back-Propagation method, after features extraction of the eye and mouth is performed, the result of the feature extraction, will later be used to detect a person drowsy or not, for other research.


Feature Extraction; Frame Extraction; Neural Network; Back-Propagation


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