Object recognition of ladar with support vector machine

Jian-Feng Sun; Qi Li; Qi Wang

doi:10.1117/12.573763

10 January 2005 Object recognition of ladar with support vector machine

Jian-Feng Sun, Qi Li, Qi Wang

Proceedings Volume 5640, Infrared Components and Their Applications; (2005) https://doi.org/10.1117/12.573763
Event: Photonics Asia, 2004, Beijing, China

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.

Citation Download Citation

Jian-Feng Sun, Qi Li, and Qi Wang "Object recognition of ladar with support vector machine", Proc. SPIE 5640, Infrared Components and Their Applications, (10 January 2005); https://doi.org/10.1117/12.573763

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