Development of an awakening detection system with the NN and adaptation for fluctuation of brightness quantity in the captured image
by Nobuhisa Yamanaka, Hironobu Satoh, Fumiaki Takeda
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 9, No. 3/4, 2010

Abstract: Recently, accidents such that seniors fall down from the bed in hospitals are increased. To prevent these accidents, we have developed an awakening detection system using neural network. In this paper, we adopt a face extractive method to execute more detail extraction of the objective person's image from the background. We show its feasibility with experimental results. In addition, to confirm the detection capability in the clinical site, the detection experiment using the captured image in the clinical site is conducted. From the result, the detection success rate was low. So, we analyse the captured image in the clinical site. From the analysis of the histogram, it proves that the fluctuation of brightness quantity make decrease the detection capability. Therefore, to decrease this influence, the histogram of the captured image is equalised. Finally, it is verified that the histogram equalisation reduces the effect of fluctuation of brightness quantity.

Online publication date: Thu, 04-Nov-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Systems Technologies and Applications (IJISTA):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com