Drowsy driver mobile application: Development of a novel scleral-area detection method
| Autor: | Kausalendra Mahadas, George K. Hung, Faisal Mohammad |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Male
Automobile Driving Java Computer science Poison control Health Informatics Image processing 050105 experimental psychology ALARM Software 0502 economics and business Image Processing Computer-Assisted Humans 0501 psychology and cognitive sciences Computer vision computer.programming_language 050210 logistics & transportation Pixel business.industry 05 social sciences Mobile Applications Computer Science Applications Haar-like features Sleep Stages Artificial intelligence business computer Mobile device Sclera |
| Zdroj: | Computers in Biology and Medicine. 89:76-83 |
| ISSN: | 0010-4825 |
| DOI: | 10.1016/j.compbiomed.2017.07.027 |
| Popis: | A reliable and practical app for mobile devices was developed to detect driver drowsiness. It consisted of two main components: a Haar cascade classifier, provided by a computer vision framework called OpenCV, for face/eye detection; and a dedicated JAVA software code for image processing that was applied over a masked region circumscribing the eye. A binary threshold was performed over the masked region to provide a quantitative measure of the number of white pixels in the sclera, which represented the state of eye opening. A continuously low white-pixel count would indicate drowsiness, thereby triggering an alarm to alert the driver. This system was successfully implemented on: (1) a static face image, (2) two subjects under laboratory conditions, and (3) a subject in a vehicle environment. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect