Name
Abstract | ||
|---|---|---|
The process of staircase negotiation is complex for blinds. Therefore, an intelligent system is required to help them. In this paper, we investigate using only one ultrasonic sensor to detect and recognize floor and stair cases in electronic white cane. The performance of an object recognition system depends on both object representation and classification algorithms. In our system, we have used more than one representation of ultrasonic signal in frequencial domain. First, spectrogram representation explains how the spectral density of ultrasonic signal varies with time. Second, spectrum representation shows the amplitudes as a function of the frequency. Finally, periodogram representation estimates the spectral density of ultrasonic signal. Then, several features are extracted from each representation. Our system was evaluated on a set of ultrasonic signal where floor and stair cases occur with different shape. Using a multiclass SVM approach, accuracy rates of 72.41% has been achieved. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TSP.2013.6614021 | Telecommunications and Signal Processing |
Keywords | Field | DocType |
acoustic signal detection,feature extraction,object recognition,support vector machines,ultrasonic applications,electronic white cane,feature extraction,intelligent system,multiclass SVM approach,object classification algorithms,object recognition system,object representation algorithms,periodogram representation,spectral density,spectrum representation,stair case detection,stair case recognition,staircase negotiation process,ultrasonic sensor,ultrasonic signal representation,ultrasonic signal spectral density,Ultrasonic signal processing,frequencial representation of ultrasonic signal,ground-stair classification,temporal representation of ultrasonic signal | Computer vision,Ultrasonic sensor,Pattern recognition,Spectrogram,Computer science,Support vector machine,Feature extraction,Spectral density,Artificial intelligence,Statistical classification,Amplitude,Cognitive neuroscience of visual object recognition | Conference |
ISBN | Citations | PageRank |
978-1-4799-0402-0 | 2 | 0.43 |
References | Authors | |
7 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sonda Ammar Bouhamed | 1 | 2 | 0.43 |
| Kallel, I.K. | 2 | 4 | 3.87 |
| Dorra Sellami Masmoudi | 3 | 2 | 0.43 |