Rotation invariant indexing of shapes and line drawings Michail Vlachos, Zografoula Vagena, Philip S. Yu, and Vassilis Athitsos   View Paper (PDF)   Return to KM-2 (Knowledge Management): Index Structures Abstract We present data representations, distance measures and organizational structures for fast and efficient retrieval of similar shapes in image databases. Using the Hough Transform we extract shape signatures that correspond to important features of an image. The new shape descriptor is robust against line discontinuities and takes into consideration not only the shape boundaries, but also the content inside the object perimeter. The object signatures are eventually projected into a space that renders them invariant to translation, scaling and rotation. In order to provide support for real-time query-by-content, we also introduce an index structure that hierarchically organizes compressed versions of the extracted object signatures. In this manner we can achieve a significant performance boost for multimedia retrieval. Our experiments suggest that by exploiting the proposed framework, similarity search in a database of 100,000 images would require under 1 sec, using an off-the-shelf personal computer. ©2006 Association for Computing Machinery