A Fast Algorithm for Reconstructing hv-Convex Binary Images from Their Horizontal Projection

被引：0

作者：

Hantos, Norbert ^{[1
]}

Balazs, Peter ^{[2
]}

机构：

[1] Eotvos Lorand Univ, Dept Algorithms & Their Applicat, H-1117 Budapest, Hungary

[2] Univ Szeged, Dept Image Proc & Comp Graph, H-6720 Szeged, Hungary

来源：

ADVANCES IN VISUAL COMPUTING (ISVC 2014), PT II | 2014年 / 8888卷

关键词：

discrete tomography; reconstruction; connectedness; hv-convexity; polynomial-time algorithm; DISCRETE SETS; ORTHOGONAL PROJECTIONS; VERTICAL PROJECTIONS; POLYOMINOES;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The reconstruction of certain types of binary images from their projections is a frequently studied problem in combinatorial image processing. hv-convex images with fixed projections play an important role in discrete tomography. In this paper, we provide a fast polynomialtime algorithm for reconstructing canonical hv-convex images with given number of 4-connected components and with minimal number of columns satisfying a prescribed horizontal projection. We show that the method gives a solution that is always 8-connected. We also explain how the algorithm can be modified to obtain solutions with any given number of columns, and also with non-connected components.

引用

页码：789 / 798

页数：10

共 23 条

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