The Effect of Sub-Sampling in Scale Space Texture Classification Using Combined Classifiers
Textures show multi-scale properties and hence multiresolution techniques are considered appropriate for texture classification. Recently, the authors proposed a multiresolution texture classification system based on scale space theory and combined classifiers. However, the use of multiresolution te...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2007
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| Subjects: | |
| Online Access: | http://shdl.mmu.edu.my/3214/ |
| Summary: | Textures show multi-scale properties and hence multiresolution techniques are considered appropriate for texture classification. Recently, the authors proposed a multiresolution texture classification system based on scale space theory and combined classifiers. However, the use of multiresolution techniques increases the computational load and memory space required. Sub-sampling can help to reduce these side effects of multiresolution techniques. However, it may degrade the overall performance of the classification system. In this paper the effect of sub-sampling is investigated in scale space texture classification using combined classifiers. It is shown that sub-sampling can help to reduce both computational load and memory space required without compromising the performance of the system. |
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