Fatigue Detection Using Computer Vision

Abstract

Fatigue Detection Using Computer VisionLong duration driving is a significant cause of fatigue related accidents of cars, airplanes, trains and other means of transport. This paper presents a design of a detection system which can be used to detect fatigue in drivers. The system is based on computer vision with main focus on eye blink rate. We propose an algorithm for eye detection that is conducted through a process of extracting the face image from the video image followed by evaluating the eye region and then eventually detecting the iris of the eye using the binary image. The advantage of this system is that the algorithm works without any constraint of the background as the face is detected using a skin segmentation technique. The detection performance of this system was tested using video images which were recorded under laboratory conditions. The applicability of the system is discussed in light of fatigue detection for drivers.

Rearranged DCT Feature Analysis Based on Corner Patches for CBIR (contents based image retrieval)

“…As visual systems have been combined with areas of intelligence in moving robots [1,2], intelligent traffic system [3][4][5], and medicine [6,7], the importance of visual systems has been raised as a central technology which will contribute to human welfare and business directly.…”

“…It has been proposed a technique that uses feature parameters such as chain code [8], Zernike moment [9][10], invariant moment [7], Fourier descriptors [7] as the search technology using the shape information. Among them, a corner detection that is an important feature of the image processing and computer vision, has been studied by using method to detect corner position using the mask of circular in the image of the gray level, to analyze the distribution of the brightness, and to be crossed by using direction of the straight lines in the contour lines, etc.…”

Puzzlement Detection from Facial Expression Using Active Appearance Models and Support Vector Machines

“…However, most of these studies [10][11][12][13][14] focused on only six universal facial expressions triggered by basic emotions. The computational models that can recognize subtle facial expressions (i.e., fatigue [15,16]) are limited. Facial expressions triggered by learning-centered affective states, i.e.…”

Rearranged Hough transform based on image retrieval technique

“…As visual systems have been combined with areas of intelligence in moving robots [1,2], intelligent traffic system [3,4], and medicine [5,6], the importance of visual systems has been raised as a central technology which will contribute to human welfare and business directly. The fundamental work of a visual based system is to detect lines, corners, and curves as geometric traits in images.…”