Paper Info
Title
Possibilistic modeling of ultrasonic signal for floor state recognition
Abstract
The process of staircases detection and recognition is complex for blinds. Therefore, an intelligent and real time system is required to help them. In this paper, we investigate using only one ultrasonic sensor and few samples with small size to represent floor and staircases. The performance of such system depend on object representation, data modeling and finally classification algorithm. A simple wave analysis have shown that frequency components are the most affected in stair case context. Accordingly, we have used frequency representation of ultrasonic signal, namely the smoothed periodogram. Then, we model model several extracted features based on Masson possibility approach. Finally, similarity measure is used in the classification algorithm. A training process is under taken on a local database of 500 signal simples is used. An accuracy rate of 94% has been achieved.
Year
DOI
Venue
2014
10.1109/ATSIP.2014.6834581
ATSIP
Keywords
Field
DocType
feature extraction,floors,signal classification,signal representation,statistical distributions,ultrasonic transducers,masson possibility approach,data modeling,floor state recognition,frequency representation,intelligent system,possibilistic modeling,probability distribution,real time system,staircases detection,staircases recognition,ultrasonic sensor,ultrasonic signal classification algorithm,possibility theory,similarity,ultrasonic signal processing,uncertainty information,estimation,acoustics
Data modeling,Computer vision,Ultrasonic sensor,State recognition,Similarity measure,Computer science,Real-time operating system,Feature extraction,Probability distribution,Periodogram,Artificial intelligence
Conference
Citations 
PageRank 
References 
0
0.34
8
Authors
4
Name
Order
Citations
PageRank
Bouhamed, S.A.100.34
Kallel, I.K.243.87
Masmoudi, D.S.300.34
Basel Solaiman412735.05