The flat zone approach: A general low-level region merging segmentation method

被引:69
作者
Crespo, J
Schafer, RW
Serra, J
Gratin, C
Meyer, F
机构
[1] Departamento LSIIS, Grupo de Informatisa Medica - LIA, Univ. Pulitécnica de Madrid
[2] School of Electrical Engineering, Georgia Institute of Technology, Atlanta
[3] Ctr. de Morphol. Mathématique, École des Mines de Paris, 77305 Fontainebleau
[4] A.D.C.I.S., 14000 Caen, 7, rue Alfred Kastler
关键词
flat zone approach; segmentation; graph; mathematical morphology; watershed;
D O I
10.1016/S0165-1684(97)00114-X
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
This paper presents a segmentation method, the flat zone approach, that avoids some limitations of the watershed-plus-markers method. The watershed-plus-markers approach, which is the traditional segmentation technique in mathematical morphology, has two inherent problems: (1) the possible separation of a piecewise-constant region of the input image into several regions in the output partition, and (2) the problem of obtaining markers (connected components of pixels signaling significant regions) for features that are one or two pixels wide. These problems are related to the limited resolution power (for feature extraction) of gradient operators. The hat zone approach extends the region marker concept (to contain the entire (and not part of) regions) and requires neither the computation of a gradient function nor the modification of the support of the input image in order to increase the size of the features. Our approach works on the graph formed by the image flat zones (or piecewise-constant regions). This fact ensures that the input image regions are not broken and can consider all input flat zones regardless their size. An inclusion relationship between the flat zones of the input image and the regions of the output partition is imposed. That is, a flat zone segmentation method is a region (flat zone) merging method and behaves like a connected operator. Our method is robust (in the sense that it is invariant under certain intensity value transformations) and uses a hierarchical waiting queue algorithm that makes it extremely efficient. (C) 1997 Elsevier Science B.V.
引用
收藏
页码:37 / 60
页数:24
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