Number of the records: 1  

Query by Pictorial Example

  1. 1.
    0359019 - ÚTIA 2012 CZ eng D - Thesis
    Vácha, Pavel
    Query by Pictorial Example.
    UTIA AV CR. Defended: MFF UK Praha. 5.4.2011. - Praha: MFF UK, 2010. 171 s.
    R&D Projects: GA MŠMT 1M0572; GA AV ČR 1ET400750407; GA AV ČR IAA2075302; GA ČR GA102/08/0593
    Institutional research plan: CEZ:AV0Z10750506
    Keywords : texture * illuminatin invariants * rotation invariants * Markov random fields * content based image retrieval
    Subject RIV: BD - Theory of Information

    Ongoing expansion of digital images requires new methods for sorting, browsing, andsearching through huge image databases. This is a domain of Content-Based Image Retrieval (CBIR) systems, which are database search engines for images. A user typically submit a query image or series of images and the CBIR system tries to find and to retrieve the most similar images from the database. Optimally, the retrieved images should not be sensitive to circumstances during their acquisition. Unfortunately, the appearance of natural objects and materials is highly illumination and viewpoint dependent. This work focuses on representation and retrieval of homogeneous images, called textures, under the circumstances with variable illumination and texture rotation. We propose a novel illumination invariant textural features based on Markovian modelling of spatial texture relations.
    Permanent Link: http://hdl.handle.net/11104/0196897

     
     
Number of the records: 1  

  This site uses cookies to make them easier to browse. Learn more about how we use cookies.