Adaptive classification for image segmentation and target recognition

被引:0
|
作者
Bargel, B [1 ]
Bers, KH [1 ]
Jäger, K [1 ]
Schwan, G [1 ]
机构
[1] FGAN FOM, Forschungsinst Optron & Mustererkennug, Res Inst Optron & Pattern Recognit, D-76275 Ettlingen, Germany
来源
关键词
autonomous systems; pattern recognition; model based structural analysis; image segmentation; texture elements; feature space partitioning; presetting and initialization; adaptive classification; screening; regions of interest; image compression;
D O I
10.1117/12.477031
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper on adaptive image segmentation and classification describes research activities on statistical pattern recognition in combination with methods of object recognition by geometric matching of model and image structures. In addition, aspects of sensor fusion for airborne application systems like terminal missile guidance were considered using image sequences of multispectral data from real sensor systems and from computer simulations. The main aspect of the adaptive classification is the support of model-based structural image analysis by detection of image segments representing specific objects, e.g. forests, rivers and urban areas. The classifier, based on textural features, is automatically adapted to the changes of textural signatures during target approach by interpretation of the segmentation results of each actual frame of the image sequence.
引用
收藏
页码:230 / 240
页数:11
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