Enhanced Clustering Algorithms For Gray-Scale Image Segmentation
The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. The algorithms are chosen since they are easy to be implemented, required low computational time and less sensitive to noise and artifacts. Howeve...
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| المؤلف الرئيسي: | |
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| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2012
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.usm.my/41804/1/FASAHAT_ULLAH_SIDDIQUI.pdf |
| الوسوم: |
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| الملخص: | The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. The algorithms are chosen since they are easy to be implemented, required low computational time and less sensitive to noise and artifacts. However, in some cases the conventional clustering algorithms introduce over-segmentation problems and unable to preserve the region of interest (i.e. objects). |
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