Open AccessRegion matching based on colour invariants in rgb orthogonal space
Author(s) -
Cui Xintong,
Kan Jiangming,
Li Wenbin
Publication year - 2016
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2015.0020
Subject(s) - rgb color model , invariant (physics) , artificial intelligence , mathematics , computer vision , matching (statistics) , pattern recognition (psychology) , rgb color space , space (punctuation) , image (mathematics) , computer science , color image , image processing , statistics , mathematical physics , operating system
Illumination influences the performance of region feature matching based on a grey image. A novel region‐matching algorithm based on the colour invariants and colour‐invariant moments in rgb orthogonal colour space is proposed. First, a colour image is converted in RGB colour space to rgb orthogonal colour space that has colour invariance. Second, the colour invariants H and C λ are calculated. Then, the maximally stable extremal region is extracted from the colour invariants and the colour‐invariant moments are computed. Finally, the nearest neighbour method is used to find corresponding regions. The proposed method can take advantage of both the colour and geometric properties of the images to solve the problem of illumination influences. Experimental results from the Amsterdam Library of Object Images database and images captured on the Beijing Forestry University campus show that performance of the proposed algorithm is better than that of prior art methods.