Open AccessMorphological estimates of image complexity and information content
Author(s) -
S. A. Brianskiy,
Yu. V. Vizilter
Publication year - 2018
Publication title -
kompʹûternaâ optika
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.491
H-Index - 29
eISSN - 2412-6179
pISSN - 0134-2452
DOI - 10.18287/2412-6179-2018-42-3-501-509
Subject(s) - mathematical morphology , image (mathematics) , artificial intelligence , tessellation (computer graphics) , computer science , pattern recognition (psychology) , content (measure theory) , mosaic , computational complexity theory , computer vision , mathematics , image processing , algorithm , geography , computer graphics (images) , mathematical analysis , archaeology
We propose new morphological conditional estimates of image complexity and information content as well as morphological mutual information. These morphological estimates take into account both the number and the shape of image tessellation (mosaic) regions. We provide such a region shape account via joint use of mosaic image shape models based on the morphological image analysis (MIA) proposed by Yu. Pyt’ev and morphological thickness maps from the mathematical morphology (MM) introduced by J. Serra. Mathematical properties of morphological thickness maps are explored w.r.t. properties of structured elements, and corresponding properties of the proposed morphological image complexity and information content are proved. Some experimental results on image shape comparison in terms of shape complexity and information are reported. Open access images from a Kimia99 database are utilized for these experiments.