REAL TIME DROWSINESS DETECTION USING DIFFERENT EDGE DETECTION TECHNIQUES

A Real Time Driver Drowsiness Detection System

Driving with drowsiness is one of the main causes of traffic accidents. Driver fatigue is a significant factor in a large number of vehicle accidents. The development of technologies for detecting or preventing drowsiness at the wheel is a major challenge in the field of accident avoidance systems. Due to the hazard that drowsiness presents on the road, methods need to be developed for countera...

Real-time Nonintrusive Detection of Driver Drowsiness

Driver drowsiness is one of the major causes of serious traffic accidents, which makes this an area of great socioeconomic concern. Continuous monitoring of drivers’ drowsiness thus is of great importance to reduce drowsiness-caused accidents. This proposed research developed a real-time, nonintrusive driver drowsiness detection system by building biosensors on the automobile steering wheel and...

Real Time Edge Detection Using DSP Processor

Edge detection from images is one of the most important concerns in digital image and video processing. Edge detection is very useful in computer vision for extracting meaningful information from images. Real time edge detection is implemented on the platform that consists of the TMS320DM6437 DSP, camera, TV tuner, Display and canny edge detection algorithm. The main goal of our technique is to...

Real Time Driver’s Drowsiness Detection by Processing the EEG Signals Stimulated with External Flickering Light

The objective of this study is development of driver’s sleepiness using Visually Evoked Potentials (VEP). VEP computed from EEG signals from the visual cortex. We use the Steady State VEPs (SSVEPs) that are one of the most important EEG signals used in human computer interface systems. SSVEP is a response to visual stimuli presented. We present a classification method to discriminate between...

Detection of Congenital Mullerian Anomalies Using Real-Time 3D Sonography