15th International Conference on Pattern Recognition (ICPR'00) - Volume 1 An Invariant Local Vector for Content-Based Image Retrieval Barcelona, Spain September 03-September 08 ISBN: 0-7695-0750-6
In this paper, we present the use of Full-Zernike moments as a local characterization of the image signal. Their computation allows us to construct a locally invariant vector, of which the projection in an index table provides a vote for some model-image. This approach is based on the quasi-invariant theory applied to perspective transformation. Then it requires a characterization being invariant to translation, rotation and change of scale in the image; in other respect, an appropriate normalization of the signal delivers invariance to illuminance conditions.
Citation:
Erwan Bigorgne, Catherine Achard, Jean Devars, "An Invariant Local Vector for Content-Based Image Retrieval," icpr, vol. 1, pp.5019, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 1, 2000 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||