6533b839fe1ef96bd12a6d7c

RESEARCH PRODUCT

New methods for analysing colour texture based on the Karhunen–Loeve transform and quantification

Pierre GoutonFrederic TruchetetJean-christophe DevauxIrène Foucherot

subject

Karhunen–Loève theoremLocal linearbusiness.industryExtension (predicate logic)Texture (geology)Co-occurrence matrixArtificial IntelligenceSignal ProcessingComputer visionComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareMathematics

description

In this article, we offer an original study on the analysis of the texture of colour images based on Local Linear Transforms (LLT). Our colour approach is based on the separability of the data which reduces the number of texture parameters. We also propose the extension of Run Lengths (RL) and Co-occurrence Matrixes (CM) to colour images. In this respect, two different ways were explored (data merging and quantification). We finally present a comparative study showing the efficiency of the first method (LLT) as well as the complementary nature of the other methods (RL, CM).

yearjournalcountryeditionlanguage
2004-08-01Pattern Recognition
https://doi.org/10.1016/j.patcog.2004.02.010