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.
| Original language | English |
|---|---|
| Article number | 72 |
| Pages (from-to) | 434-439 |
| Number of pages | 6 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 5640 |
| DOIs | |
| State | Published - 2005 |
| Event | Infrared Components and their Applications - Beijing, China Duration: 8 Nov 2004 → 11 Nov 2004 |
Keywords
- Laser radar
- Support vector machine
- Target recognition
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