Adaptive Centroid Placement Based SNIC for Superpixel Segmentation

被引：0

作者：

Senanayaka, Janith Bandara ^{[1
]}

Morawaliyadda, Dilshan Thilanka ^{[1
]}

Senarath, Shehan Tharuka ^{[1
]}

Godaliyadda, Roshan Indika ^{[1
]}

Ekanayake, Mervyn Parakrama ^{[1
]}

机构：

[1] Univ Peradeniya, Dept Elect & Elect Engn, Peradeniya, Sri Lanka

来源：

MERCON 2020: 6TH INTERNATIONAL MULTIDISCIPLINARY MORATUWA ENGINEERING RESEARCH CONFERENCE (MERCON) | 2020年

关键词：

Image segmentation; superpixels; SNIC; mean shift; entropy; MEAN SHIFT;

D O I：

10.1109/mercon50084.2020.9185361

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The proposed image segmentation algorithm identifies information-rich versus low information regions based on surface entropy. Thereafter on the information-rich regions, the mean shift algorithm is applied to generate possible centroid initialization points. This enables the Simple Non-Iterative Clustering (SNIC) algorithm when initialized through the proposed mechanism to provide more concentrated segmentation in those information-rich regions and sparse segmentation in the low information regions.

引用

页码：242 / 247

页数：6

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