Distortion-tolerant object classification using photon counting three-dimensional integral imaging

被引：0
|
作者：
Yeom, Seokwon [1 ]
Javidi, Bahram [2 ]
Watson, Edward [3 ]
机构：
[1] Daegu Univ, Sch Comp & Commun Sci, Gyongsan 712714, Gyeongbuk, South Korea
[2] Univ Connecticut, Dept Elect & Comp Engn, Storrs, CT 06269 USA
[3] US Air Force, Res Labs, Wright Patterson AFB, OH 45433 USA
来源：
THREE-DIMENSIONAL TV, VIDEO, AND DISPLAY VI | 2007年 / 6778卷
关键词：
automatic target recognition; pattern recognition and feature extraction; rotation-invariant pattern recognition; three-dimensional image processing; photon counting; integral imaging;
D O I：
10.1117/12.732362
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we address distortion-tolerant object recognition using photon-counting three-dimensional (3D) integral imaging (II). A photon-counting linear discriminant analysis (LDA) is reviewed for classification of out-of-plane rotated objects. We also investigate the effect of a large number of photons and the irradiance change in training and test objects.
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页数：6
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