A Convexity Measure for Gray-Scale Images Based on hv-Convexity

被引:0
|
作者
Bodnar, Peter [1 ]
Balazs, Peter [1 ]
Nyul, Laszlo G. [1 ]
机构
[1] Univ Szeged, Dept Image Proc & Comp Graph, Arpad Ter 2, H-6720 Szeged, Hungary
来源
IMAGE ANALYSIS AND PROCESSING,(ICIAP 2017), PT I | 2017年 / 10484卷
关键词
Convexity measure; Digital geometry; hv-convexity; Gray-scale convexity; DISCRETE TOMOGRAPHY; RECONSTRUCTION; PROJECTIONS; POLYOMINOES; POLYGONS;
D O I
10.1007/978-3-319-68560-1_52
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
There are several measures for the convexity of digital images that extend the basic binary decision of the classic geometrical convexity. Some algorithms measure the convexity of a binary image using intensity profiles from horizontal and vertical directions. In this paper, we generalize the idea of binary, directional convexity and evaluate the proposed algorithm on gray-scale images. Furthermore, instead of a single convexity value, a vector can be formed using our approach, which provides a more prominent feature for various applications, such as computer vision, classification, retrieval, or medical image processing. The proposed feature can also be used locally on image parts, which makes that applicable as a shape descriptor.
引用
收藏
页码:586 / 594
页数:9
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