| TR#: | CIS9701 |
| Class: | CIS |
| Title: | Shape Retrieval in Pictorial Databases via Geometric Features |
| Authors: | Michael Kliot and Ehud Rivlin |
| CIS9701.pdf | |
| Abstract: | We describe a new approach for shape-based retrieval in image databases. The approach relies on contours description of the image shape, and emphasizes the use of invariants. Efficient indexing is based on geometric invariant features, while semi-local multi-valued invariant signatures are used for ranking the answers. The advantages of the proposed approach are its ability to retrieve images in situations in which part of the shape is missing (i.e., in case of occlusion or sketch queries), its ability to handle images distorted by different viewpoint transformations, and its ability to flexibly answer queries based on logical or shape descriptions (query by example), or on combination of both. The approach can handle sketch based queries, and algorithms for such queries are presented. We have developed a data model in accordance with our proposed approach, and implemented it in an object oriented database system with a SQL-like user interface. The database consists of 398 images of logos and trademarks. The paper presents experimental results demonstrating the effectiveness of the proposed approach. |
| Copyright | The above paper is copyright by the Technion, Author(s), or others. Please contact the author(s) for more information |
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