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Extended set of superpixel features
A.A. Egorova 1, V.V. Sergeyev 1,2

Samara National Research University, 443086, Samara, Russia, Moskovskoye Shosse 34,
IPSI RAS – Branch of the FSRC "Crystallography and Photonics" RAS,
443001, Samara, Russia, Molodogvardeyskaya 151

 PDF, 1441 kB

DOI: 10.18287/2412-6179-CO-876

Pages: 562-574.

Full text of article: Russian language.

Abstract:
Superpixel-based image processing and analysis methods usually use a small set of superpixel features. Expanding the description of superpixels can improve the quality of processing algorithms. In the paper, a set of 25 basic superpixel features of shape, intensity, geometry, and location is proposed. The features meet the requirements of low computational complexity in the process of image superpixel segmentation and sufficiency for solving a wide class of application tasks. Applying the set, we present a modification of the well-known approach to the superpixel generation. It consists of fast primary superpixel segmentation of the image with a strict homogeneity predicate, which provides superpixels preserving the intensity information of the original image with high accuracy, and the subsequent enlargement of the superpixels with softer homogeneity predicates. The experiments show that the approach can significantly reduce the number of image elements, which helps to reduce the complexity of processing algorithms, meanwhile the expanded superpixels more accurately correspond to the image objects.

Keywords:
superpixel segmentation, feature, invariant moments, polynomial approximation.

Citation:
Egorova AA, Sergeyev VV. Extended set of superpixel features. Computer Optics 2021; 45(4): 562-574. DOI: 10.18287/2412-6179-CO-876.

Acknowledgements:
This work was supported by the Russian Foundation for Basic Research under project No. 19-37-90116 and the Russian Federation Ministry of Science and Higher Education within a state contract with the "Crystallography and Photonics" Research Center of the RAS under agreement 007-ГЗ/Ч3363/26.

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