6533b861fe1ef96bd12c590e

RESEARCH PRODUCT

Texture classification for content-based image retrieval

Roberto Pirrone 6M. La Cascia

subject

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniContextual image classificationComputer sciencebusiness.industryFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionImage segmentationContent-based image retrievalCBIR texture analysisObject detectionImage textureFeature (computer vision)Computer visionArtificial intelligencebusinessImage retrieval

description

An original approach to texture-based classification of regions, for image indexing and retrieval, is presented. The system addresses automatic macro-textured ROI detection, and classification: we focus our attention on those objects that can be characterized by a texture as a whole, like trees, flowers, walls, clouds, and so on. The proposed architecture is based on the computation of the /spl lambda/ vector from each selected region, and classification of this feature by means of a pool of suitably trained support vector machines (SVM). This approach is an extension of the one previously developed by some of the authors to classify image regions on the basis of the geometrical shape of the objects they contain. Theoretical remarks, motivation of the approach, experimental setup, and the first satisfactory results on natural scenes are reported.

yearjournalcountryeditionlanguage
2002-11-13Proceedings 11th International Conference on Image Analysis and Processing
https://doi.org/10.1109/iciap.2001.957042