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Proceedings Paper

Object recognition of ladar with support vector machine
Author(s): Jian-Feng Sun; Qi Li; Qi Wang
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Paper Abstract

Intensity, range and Doppler images can be obtained by using laser radar. Laser radar can detect much more object information than other detecting sensor, such as passive infrared imaging and synthetic aperture radar (SAR), so it is well suited as the sensor of object recognition. Traditional method of laser radar object recognition is extracting target features, which can be influenced by noise. In this paper, a laser radar recognition method-Support Vector Machine is introduced. Support Vector Machine (SVM) is a new hotspot of recognition research after neural network. It has well performance on digital written and face recognition. Two series experiments about SVM designed for preprocessing and non-preprocessing samples are performed by real laser radar images, and the experiments results are compared.

Paper Details

Date Published: 10 January 2005
PDF: 6 pages
Proc. SPIE 5640, Infrared Components and Their Applications, (10 January 2005); doi: 10.1117/12.573763
Show Author Affiliations
Jian-Feng Sun, Harbin Institute of Technology (China)
Qi Li, Harbin Institute of Technology (China)
Qi Wang, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 5640:
Infrared Components and Their Applications
Haimei Gong; Yi Cai; Jean-Pierre Chatard, Editor(s)

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