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Technical Program
Paper Detail
| Paper: | TA-L1.8 |
| Session: | Image Segmentation |
| Time: | Tuesday, October 10, 12:20 - 12:40 |
| Presentation: |
Lecture
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| Title: |
WEIGHTED VOTING-BASED ROBUST IMAGE THRESHOLDING |
| Authors: |
Shahryar Rahnamayan; University of Waterloo | | | | | Hamid R. Tizhoosh; University of Waterloo | | | | | Magdy M. A. Salama; University of Waterloo | | |
| Abstract: |
A new robust image thresholding technique is introduced in this paper. Comprehensive experiments show that a single thresholding method can not be successful for all kind of images. The proposed approach uses fusion of some well-known thresholding methods by applying weighted voting at the decision level. The main objective is improving robustness of thresholding approach by participating several methods. Although, the proposed approach can not guaranty the best result for all kind of images but it shows higher performance and consistent/smoother behavior in overall. The performance of the new approach and nine well-established thresholding methods are compared by applying to an image set with high image diversity. The comparison results show that the proposed approach outperforms other nine well-established thresholding approaches. The proposed approach has been explained in details and experimental results are provided. |
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