A new information-theoretic distance measure for images is proposed. The measure is based on the concept of average common sub-matrix by considering the pixel matrices associated with the images. An algorithm to compute such a value is described, and its computational complexity analyzed. Experimental results show that the measure is able to discriminate images by correctly reflecting human perception. Furthermore, comparison with state-of-the-art information-theoretic measures, points out that the new measure outperforms these measures in terms of retrieval precision. © 2013 Springer-Verlag.

Average common submatrix: A new image distance measure

Amelio A.;
2013-01-01

Abstract

A new information-theoretic distance measure for images is proposed. The measure is based on the concept of average common sub-matrix by considering the pixel matrices associated with the images. An algorithm to compute such a value is described, and its computational complexity analyzed. Experimental results show that the measure is able to discriminate images by correctly reflecting human perception. Furthermore, comparison with state-of-the-art information-theoretic measures, points out that the new measure outperforms these measures in terms of retrieval precision. © 2013 Springer-Verlag.
2013
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Inglese
17th International Conference on Image Analysis and Processing, ICIAP 2013
2013
Naples, ita
8156
170
180
11
978-3-642-41180-9
978-3-642-41181-6
image retrieval; pattern matching; similarity measure
no
none
Amelio, A.; Pizzuti, C.
273
info:eu-repo/semantics/conferenceObject
2
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/770238
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