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Description
  • The availability of various photo archives and photo sharing systems made similarity searching much more important because the photos are not usually conveniently tagged. So the photos (images) need to be searched by their content. Moreover, it is important not only to compare images with a query holistically but also to locate images that contain the query as their part. The query can be a picture of a person, building, or an abstract object and the task is to retrieve images of the query object but from a different perspective or images capturing a global scene containing the query object. This retrieval is called the sub-image searching. In this paper, we propose an algorithm for retrieving database images by their similarity to and containment of a query. The novelty of it lies in application of a sequence alignment algorithm, which is commonly used in text retrieval. This forms an orthogonal solution to currently used approaches based on inverted files.
  • The availability of various photo archives and photo sharing systems made similarity searching much more important because the photos are not usually conveniently tagged. So the photos (images) need to be searched by their content. Moreover, it is important not only to compare images with a query holistically but also to locate images that contain the query as their part. The query can be a picture of a person, building, or an abstract object and the task is to retrieve images of the query object but from a different perspective or images capturing a global scene containing the query object. This retrieval is called the sub-image searching. In this paper, we propose an algorithm for retrieving database images by their similarity to and containment of a query. The novelty of it lies in application of a sequence alignment algorithm, which is commonly used in text retrieval. This forms an orthogonal solution to currently used approaches based on inverted files. (en)
Title
  • Searching for Sub-images using Sequence Alignment
  • Searching for Sub-images using Sequence Alignment (en)
skos:prefLabel
  • Searching for Sub-images using Sequence Alignment
  • Searching for Sub-images using Sequence Alignment (en)
skos:notation
  • RIV/00216224:14330/11:00049949!RIV12-MV0-14330___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA201/09/0683), P(GAP103/10/0886), P(VF20102014004), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 228474
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/11:00049949
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • image matching; sub-image retrieval; local image features; sequence alignment (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [A7A99EFDE066]
http://linked.open...v/mistoKonaniAkce
  • Dana Point, California, USA
http://linked.open...i/riv/mistoVydani
  • Los Alamitos, California
http://linked.open...i/riv/nazevZdroje
  • IEEE International Symposium on Multimedia (ISM 2011)
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Zezula, Pavel
  • Homola, Tomáš
  • Dohnal, Vlastislav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/ISM.2011.19
http://purl.org/ne...btex#hasPublisher
  • IEEE Computer Society
https://schema.org/isbn
  • 978-1-4577-2015-4
http://localhost/t...ganizacniJednotka
  • 14330
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