Face and Hand Gesture Recognition for Physical Impairment People Using Nn-classification

Physically disabled and mentally challenged people are an important part of the society that has not yet received the same opportunities as others in their inclusion in the Information Society. Therefore, it is necessary to develop easily accessible systems for computers to achieve their inclusion within the new technologies. The paper presents a method whose objective is to draw disabled people nearer to new technologies. It presents a vision-based user interface designed to achieve computer accessibility for disabled users with motor impairments. The interface automatically finds the user’s face and tracks it through time to recognize gestures within the face region in real time and also implement vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of the paper is to develop robust and efficient hand segmentation algorithm where three algorithms for hand segmentation using different color spaces with required thresholds have were utilized. Hand tracking and segmentation algorithm is found to be most efficient to handle the challenges of vision based system such as skin color detection, complex background removal and variable lighting condition. Noise may contain, sometime, in the segmented image due to dynamic background. Tracking algorithm has developed and applied on the segmented hand contour for removal of unwanted background noise.