Multiscale connected operators

被引:14
作者
Braga-Neto, U [1 ]
机构
[1] Fiocruz MS, Virol & Expt Therapy Lab, Aggeu Magalhaes Res Ctr, CPqAM, BR-50670420 Recife, PE, Brazil
关键词
connectivity; connectivity classes; connected operators; multiscale connectivity; grain operators; flattenings; levelings; image analysis; scale-space; granulometry; pattern spectrum; granulometric analysis; automatic target recognition;
D O I
10.1007/s10851-005-4890-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Among the major developments in Mathematical Morphology in the last two decades are the interrelated subjects of connectivity classes and connected operators. Braga-Neto and Goutsias have proposed an extension of the theory of connectivity classes to a multiscale setting, whereby one can assign connectivity to an object observed at different scales. In this paper, we study connected operators in the context of multiscale connectivity. We propose the notion of a sigma-connected operator, that is, an operator connected at scale sigma. We devote some attention to the study of binary sigma-grain operators. In particular, we show that families of sigma-grain openings and sigma-grain closings, indexed by the connectivity scale parameter, are granulometries and anti-granulometries, respectively. We demonstrate the use of multiscale connected operators with image analysis applications. The first is the scale-space representation of grayscale images using multiscale levelings, where the role of scale is played by the connectivity scale. Then we discuss the application of multiscale connected openings in granulometric analysis, where both size and connectivity information are summarized. Finally, we describe an application of multiscale connected operators to an automatic target recognition problem.
引用
收藏
页码:199 / 216
页数:18
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