In this project we aim to invent and develop new techniques for the retrieval of figurative images (such as clip art, logos, signs) from large databases. Our techniques will be based on the extraction and matching of perceptually relevant shape features, thereby overcoming many of the limitations of existing methods. This project will develop and evaluate new algorithms for:· Perceptual segmentation of raw images, and grouping of shape elements.· Matching of geometrical patterns representing shape features.· Partial matching: fitting part of one shape with part of another.· Indexing shape features in huge databases of figurative images.· Indexing the relative spatial layout of shape features within these images. The project meets the objectives of the FET programme through a highly innovative (and hence high-risk) programme to develop novel techniques for shape matching aimed at tackling one of the key problems limiting the effectiveness of current image retrieval techniques. Our project offers the possibility of significant advances at both the scientific and economic level. New in our approach is the primary role of perceptually relevant shape features, the emphasis on the unsolved problem of partial matching, and indexing over lay-out and shapes rather than over feature vectors. The newly developed algorithms will be experimentally verified in a prototype system, and subjected to rigorous evaluation on databases with independently-validated ground truth. We consider that the Profit project meets the objectives of FET Open. Specifically:
· The proposed research is inherently innovative, high-risk and long-term.
· It is embryonic research, showing proof-of concept.
· It holds out the promise of major advances at a foundational level.
Funding SchemeSTREP - Specific Targeted Research Project