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An object detection algorithm based on the cloud model

  • Yuyong Cui*
  • , Zhiyuan Zeng
  • , Liu Liu
  • *Corresponding author for this work
  • Huazhong University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Cloud model is an advanced theory for solving uncertainty problems. Taking the uncertainty of images into account, this paper proposes an object detection algorithm based on the cloud model. First, adopt cloud model theory to transform the image's qualitative model to its quantitative model. Then, use climbing policy to get different level concepts which represent different level objects. At last, compute a certainty degree and determine which concept each pixel belongs to. Experimental results proved that the algorithm can have a better effect in accuracy of detecting objects and it is good at resolving the edges of different objects.

Original languageEnglish
Title of host publicationProceedings of the 2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009
Pages910-912
Number of pages3
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009 - Sanya, Hainan, China
Duration: 24 Apr 2009 → 26 Apr 2009

Publication series

NameProceedings of the 2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009
Volume1

Conference

Conference2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009
Country/TerritoryChina
CitySanya, Hainan
Period24/04/09 → 26/04/09

Keywords

  • Cloud model
  • Image processing
  • Object detection
  • Uncertainty

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