Image classification using compression distance

Simple item page
dc.contributor.authorLan, Yuxuanen_US
dc.contributor.authorHarvey, Richarden_US
dc.contributor.editorMike Chantleren_US
dc.date.accessioned2016-02-11T13:30:56Z
dc.date.available2016-02-11T13:30:56Z
dc.date.issued2005en_US
dc.description.abstractThe normalised compression distance measures the mutual compressibility of two signals. We show that this distance can be used for classification on real images. Furthermore, the same compressor can also operate on derived features with no further modification. We consider derived features consisting of trees indicating the containment and relative area of connected sets within the image. It had been previously postulated that such trees might be useful features, but they are too complicated for conventional classifiers. The new classifier operating on these trees produces results that are very similar to those obtained on the raw images thus allowing, for the first time, classification using the full trees.en_US
dc.description.sectionheadersImage Matching, Recognition, and Retrievalen_US
dc.description.seriesinformationVision, Video, and Graphics (2005)en_US
dc.identifier.doi10.2312/vvg.20051023en_US
dc.identifier.isbn3-905673-57-6en_US
dc.identifier.pages173-180en_US
dc.identifier.urihttps://doi.org/10.2312/vvg.20051023en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.4.8 [Scene Analysis]en_US
dc.subjectObject recognitionen_US
dc.titleImage classification using compression distanceen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
173-180.pdf
Size:
849.44 KB
Format:
Adobe Portable Document Format
Download
Collections
VVG05