Split and Merge (SM) algorithm is a well recognized algorithm for segmenting homogeneous regions in an image. Though SM algorithm is simple and easy, this algorithm is unable to segment all type objects in an image successfully due to huge variations among the objects in size, shape, color and intensity. Moreover, the SM algorithm is also highly dependent on threshold values used for split and merge stages. Addressing these issues, a new algorithm namely pattern based object segmentation using split and merge (PSM) considering the basic SM algorithm, the region stability, and the patterns for object extraction. The experimental results prove the superior segmentation performance of the PSM algorithm in comparison with the basic SM algorithm, suppressed fuzzy c-means (SFCM), and object based image segmentation using fuzzy clustering (FISG)
Conference paper
Pattern based object segmentation using split and merge
pp.2166-2169
IEEE
Proceedings of Fuzzy Systems, FUZZ-IEEE2009 Conference (Jeju Island, Korea, 20-24 August)
2009
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Abstract
Details
- Title
- Pattern based object segmentation using split and merge
- Creators
- Ziaul Karim - Military Institute of Science and Technology, DhakaNafize Rabbani Paiker - Prime University, DhakaM Ameer Ali - East West UniversityGolam Sorwar - Southern Cross UniversityM M Islam - Bangladesh University of Engineering and Technology, Dhaka
- Publication Details
- pp.2166-2169
- Conference
- Proceedings of Fuzzy Systems, FUZZ-IEEE2009 Conference (Jeju Island, Korea, 20-24 August)
- Publisher
- IEEE
- Number of pages
- 2166-2169
- Identifiers
- 1407; 991012820755902368
- Academic Unit
- Faculty of Science and Engineering; Information Technology; School of Business and Tourism; Faculty of Business, Law and Arts
- Resource Type
- Conference paper