A shape-based model for visual information retrieval

Authors:
Alberto Chávez-Aragón;Oleg Starostenko
Affiliations:
Universidad Autónoma de Tlaxcala, Apizaco Tlaxcala, México;Universidad de las Américas-Puebla, Puebla, México
Venue:
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Year:
2007

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Abstract

This paper presents a novel shape-based image retrieval model. We focused on the shape feature of objects inside images because there is evidence that natural objects are primarily recognized by their shapes. Using this feature of objects the semantic gap is reduced considerably. Our technique contains an alternative representation of shapes that we have called two segment turning function (2STF). Two segment turning function has a set of invariant features such as invariant to rotation, scaling and translation. Then, based on 2STF, we proposed a complete new strategy to compute a similarity among shapes. This new method was called Star Field (SF). To test the proposed technique, which is made up of a set of new methods mentioned above, a test-bed CBIR system was implemented. The name of this CBIR System is IRONS. IRONS stands for "Image Retrieval based ON Shape". Finally, we compared our results with a set of well known methods obtained similar results without the exhaustive search of many of them. This former feature of our proposal is one of the most important contributions of our technique to the visual information retrieval area.