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http://dx.doi.org/10.5302/J.ICROS.2014.13.1965

Pillar and Vehicle Classification using Ultrasonic Sensors and Statistical Regression Method  

Lee, Chung-Su (Department of Information & Communication Engineering, Inha University)
Park, Eun-Soo (Department of Information & Communication Engineering, Inha University)
Lee, Jong-Hwan (Department of Information & Communication Engineering, Inha University)
Kim, Jong-Hee (Department of Information & Communication Engineering, Inha University)
Kim, Hakil (Department of Information & Communication Engineering, Inha University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.20, no.4, 2014 , pp. 428-436 More about this Journal
Abstract
This paper proposes a statistical regression method for classifying pillars and vehicles in parking area using a single ultrasonic sensor. There are three types of information provided by the ultrasonic sensor: TOF, the peak and the width of a pulse, from which 67 different features are extracted through segmentation and data preprocessing. The classification using the multiple SVM and the multinomial logistic regression are applied to the set of extracted features, and has achieved the accuracy of 85% and 89.67%, respectively, over a set of real-world data. The experimental result proves that the proposed feature extraction and classification scheme is applicable to the object classification using an ultrasonic sensor.
Keywords
ultrasonic sensor; object classification; logistic regression; multiple SVM;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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