| Paper: | MP-P2.8 |
| Session: | Morphological, Level-Set, and Edge or Color Image/Video Segmentation |
| Time: | Monday, September 17, 14:30 - 17:10 |
| Presentation: |
Poster
|
| Title: |
NUMBER-DRIVEN PERCEPTUAL SEGMENTATION OF NATURAL COLOR IMAGES FOR EASY DECISION OF OPTIMAL RESULT |
| Authors: |
Junji Maeda; Muroran Institute of Technology | | |
| | Akimitsu Kawano; Muroran Institute of Technology | | |
| | Sato Saga; Muroran Institute of Technology | | |
| | Yukinori Suzuki; Muroran Institute of Technology | | |
| Abstract: |
This paper proposes number-driven perceptual segmentation of natural color images using a fuzzy-based hierarchical algorithm for an easy decision of the optimal segmentation result. A fuzzy-based homogeneity measure makes a fusion of the Lab color features and the SGF texture features. Proposed hierarchical segmentation method is performed in four stages: simple splitting, local merging, global merging and boundary refinement. The effectiveness of the proposed method is confirmed through computer simulations that demonstrate an easy determination of the optimal segmentation result. |
