## Abstract Traditional content‐based image retrieval (CBIR) systems use low‐level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low‐level characteristics. Recent works on CBIR confirm that researchers
ARCHITECTURAL DRAWINGS—An Automated Indexing and Retrieval
✍ Scribed by Angela Giral
- Book ID
- 125252943
- Publisher
- The University of Chicago Press
- Year
- 1986
- Tongue
- English
- Weight
- 713 KB
- Volume
- 5
- Category
- Article
- ISSN
- 0730-7187
- DOI
- 10.2307/27947542
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
## Abstract In Japanese, the border between words is not explicitly indicated. Consequently, n‐gram (a tuple of __n__ characters) indexing is usually applied to document retrieval. Retrieval based on the n‐gram indexing is performed for long retrieval words as follows. After dividing the long retri
A content-based image retrieval mechanism to support complex similarity queries is presented. The image content is defined by three kinds of features: quantifiable features describing the visual information, nonquantifiable features describing the semantic information, and keywords describing more a