Cattle's fur detection in complex background based on Graph Cuts

Hisyam Fahmi, Ary Noviyanto, Aniati Murni Arymurthy

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

Segmentation becomes a difficult task if the objects are not homogeneous and have overlapping characteristics. The Graph Cuts methods combined with Gaussian Mixture Model (GMM) for initialization label has been adopted to detect cattle object in an image with complex background. The RGB colors and Gray Level Co-occurrence Matrix (GLCM) textures are used as the features set. This method can robustly segment the cattle beef image from its background. This segmentation method produces the average of accuracy value up to 90%.

Original languageEnglish
Pages267-271
Number of pages5
DOIs
Publication statusPublished - 1 Jan 2013
Event2013 5th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2013 - Bali, Indonesia
Duration: 28 Sep 201329 Sep 2013

Conference

Conference2013 5th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2013
Country/TerritoryIndonesia
CityBali
Period28/09/1329/09/13

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