Abstract
A two-stage mapping model (TSMM), which can be thought of as a two-levels stacked generalisation scheme for image classification, is presented. The model is proposed to bridge the semantic gap between low-level image features and high-level concepts in a divide-and-conquer manner, and aimed at minimising the gap by reducing classification errors. The idea is to design two level-0 generalisers to classify colour and texture features into colour and texture concepts respectively. Then, a level-1 generaliser is designed to classify the colour and texture concepts as middle-(words)-level concepts into high-level conceptual classes.
Original language | English |
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Pages (from-to) | 442-445 |
Number of pages | 4 |
Journal | Online Information Review |
Volume | 27 |
Issue number | 6 |
DOIs | |
State | Published - 2003 |
Keywords
- Computer graphic equipment
- Image processing
- Semantics