Detection of Drowsiness in Human Eye using SVM | Abstract

ISSN ONLINE(2320-9801) PRINT (2320-9798)

Research Article Open Access

Detection of Drowsiness in Human Eye using SVM


In Today’s world, face and eye detection play an important role in numerous security related applications. The global facial appearance depends on variation of illumination and pose in addition to, occlusion and orientation factors. In this paper a component based face detection approach using colour features is proposed. Using component based methods; the effective global facial appearance change can be overcome. In addition, the drowsy eye can be detected with alarm condition from the given images. First the eye database system is taken as the input for segmenting eyes into the right and left eye. In this segmentation process the threshold based segmentation algorithm is used. Then eyes are separated. The edge detection algorithm is used to find the open or closed eyes from the segmented eyes. The support vector machine (SVM) algorithm is used for testing and training of the segmented eye images. If the drowsy eyes are identified the alarm is to be generated for user benefits.

C. Jaya Bharathi

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