Facial expression recognition using local multidirectional score pattern descriptor and modified hidden Markov model
by Mayur Rahul; Narendra Kohli; Rashi Agarwal
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 18, No. 4, 2021

Abstract: Facial expression recognition is an application used for biometric software that can be used to recognise special expressions in a digital image by comparing and analysing different patterns. Recognising faces becomes very difficult when there is a frequent change in facial expressions. In this paper, two tier modification of normal hidden Markov model (HMM) is used to identify continuous effective facial expressions. Two tier extension of HMM: bottom and upper tier. Bottom tier represents the atomic facial expressions which are made by mouth, eyes and nose separately and upper tier represents the joint of these atomic facial expressions such as neutral, sadness etc. This paper introduces the improved modified local decision based unsymmetrical trimmed median filter (IMLDBUTMF) for noise reduction, the local multidirectional score pattern (LMSP) for feature extraction and modified hidden Markov model for classification process. The experimental result shows that the proposed method gives enhanced performance of 85% of recognition rate on publicly available datasets JAFFE.

Online publication date: Wed, 31-Mar-2021

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 Advanced Intelligence Paradigms (IJAIP):
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