Thresholding for Segmentation and Extraction of Extensive Objects on Digital Images

被引：0
|
作者：
Volkov, Vladimir [1 ]
机构：
[1] State Univ Telecommun, St Petersburg, Russia
来源：
KI 2009: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2009年 / 5803卷
关键词：
Segmentation; extraction; thresholding; erosion;
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 threshold setting problem is investigated for segmentation and extraction of extensive objects on digital images. Image processing structure is considered which includes thresholding for binarization. A new method for dynamic threshold setting and control is proposed which is based on the analysis of isolated fragment's to he extracted in the making of segmentation. Extraction of extensive objects is obtained by the use, of sequential erosion of isolated fragments on images. Number of points deleted is used for dynamic thresholding. The method proposed has optimality properties.
引用
收藏
页码：623 / 630
页数：8
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