Multi-resolution Joint Auto Correlograms: determining the distance function
Distance function plays a role in content-based image retrieval where the ideal distance function will be able to close the gap between computerised image interpretation and similarity judgment by humans. In this paper, few distance functions in relation to the advancement of Colour Auto Correl...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Published: |
IEEE
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| Online Access: | http://psasir.upm.edu.my/id/eprint/39279/ |
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| Summary: | Distance function plays a role in content-based
image retrieval where the ideal distance function will be
able to close the gap between computerised image
interpretation and similarity judgment by humans. In
this paper, few distance functions in relation to the
advancement of Colour Auto Correlogram are studied
and compared in order to determine the most suitable
distance function for the proposed Multi-resolution Joint
Auto Correlograms descriptor. An experiment has been
conducted on the SIMPLIcity image database consisting
of 1000 images where the precision, recall, and rank of
various distance functions are measured. Retrieval results
have shown that the L1-norm has achieved higher
precision rate of 78.52% and has able to rank similar
images better (a rank of 199) compared to the
Generalised Tversky Index distance function. |
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