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JOURNALS // Sibirskii Zhurnal Industrial'noi Matematiki // Archive

Sib. Zh. Ind. Mat., 2020 Volume 23, Number 1, Pages 70–83 (Mi sjim1078)

This article is cited in 4 papers

Detection of the corner structures in images by scalable masks

I. G. Kazantseva, B. O. Mukhametzhanovab, K. T. Iskakovb, T. Mirgalikyzyb

a Institute of Computational Mathematics and Mathematical Geophysics SB RAS, pr. Akad. Lavrentieva 6, Novosibirsk 630090, Russia
b The L. N. Gumilyov Eurasian National University, ul. Satpayeva 2, Nur-Sultan 010008, Kazakhstan

Abstract: Under consideration are the scalable masks for detection of corner structures in digital images which are used when processing by a window sliding through an image. The proposed matrices of masks of arbitrary size are constructed by adding rows and columns along the perimeter to the matrix of smaller masks. The submatrices remain unchanged, whereas some new elements are added by repeating the submatrix entries that preserve the structure of the corner. The algorithm can be used in processing visual data of robotics, aerial photography, and crystallography.

Keywords: image processing, sliding window, scalable mask, corner detection.

UDC: 517.562

Received: 05.06.2019
Revised: 28.11.2019
Accepted: 05.12.2019

DOI: 10.33048/SIBJIM.2020.23.107


 English version:
Journal of Applied and Industrial Mathematics, 2020, 14:1, 73–84


© Steklov Math. Inst. of RAS, 2024