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Evaluation of low-level features by decisive feature patterns.
| Content Provider | CiteSeerX |
|---|---|
| Author | Wang, Wei Zhang, Aidong |
| Abstract | In content-based image retrieval (CBIR), the effectiveness of the low-level features depends on their capabilities in describing the high-level semantic concepts. How to properly evaluate such an effectiveness remains a challenge. In this paper, we address the evaluation problem by using the decisive feature patterns of the low-level features. Intuitively, a decisive feature pattern is a combination of low-level feature values that are unique and significant for describing a semantic concept. An evaluation study on three low-level features shows that our method can tackle the evaluation problem well. That is, the decisive feature patterns can properly characterize the low-level features ’ capabilities in describing the semantic concepts. 1. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Low-level Feature Decisive Feature Pattern Low-level Feature Decisive Feature Pattern Semantic Concept Evaluation Problem Evaluation Study Low-level Feature Capability High-level Semantic Concept Content-based Image Retrieval Low-level Feature Value |
| Content Type | Text |
