Traditional Content-based image retrieval supports image searches based on color, texture and shape. However it is difficult and nonintuitive for most user to use those low level features to query images. And for most user they like search by keywords . For example , recently Google provide services in image search. Although it is named image search , but actually it is search by keywords ,not image-contents. For this reason MPEG-7 now support textual annotation standard which is MPEG-7 Multimedia Description Schemes (DSs) are metadata structures for describing and annotating audio-visual (AV) content. But manual annotation of image or video take time and expensive. we propose a system which could help us to make suitable auto-annotations.We extract the image factal features and use Diverse Density Algorithm for training models. In this way , user and system can interact in real-time . When trained models in database is growing, the system auto-annotation success rate is increasing.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0702106-211024 |
| Date | 02 July 2006 |
| Creators | Lai, Shih-jin |
| Contributors | John Y. Chiang, Chungnan Lee, Yun-lung Chang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0702106-211024 |
| Rights | off_campus_withheld, Copyright information available at source archive |
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