Abstract: Blinds people need some aid to interact with their environment with more security. A new device is then proposed to enable them to see the world with their ears. Considering not only system requirements but also technology cost, we used, for the conception of our tool, ultrasonic sensors and one monocular camera to enable user being aware of the presence and nature of potential encountered obstacles. In this paper, we are involved in using only one ultrasonic sensor to detect stair-cases in electronic cane. In this context, no previous work has considered such a challenge. Aware that the performance of an object recognition system depends on both object representation and classification algorithms, we have used in our system, one representation of ultrasonic signal in frequency domain: spectrogram representation explaining how the spectral density of signal varies with time, spectrum representation showing the amplitudes as a function of the frequency, periodogram representation estimating the spectral density of signal. Several features, thus extracted from each representation, contribute in the classification process. Our system was evaluated on a set of ultrasonic signal where stair-cases occur with different shapes. Using a multiclass SVM approach, recognition rates of 82.4% has been achieved.

Sonda Ammar Bouhamed, Imene Khanfir Kallel and Dorra Sellami Masmoudi, “New electronic white cane for stair case detection and recognition using ultrasonic sensor” International Journal of Advanced Computer Science and Applications(IJACSA), 4(6), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040633

@article{Bouhamed2013,
title = {New electronic white cane for stair case detection and recognition using ultrasonic sensor},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2013.040633},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040633},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {6},
author = {Sonda Ammar Bouhamed and Imene Khanfir Kallel and Dorra Sellami Masmoudi},
}