DocumentCode
1778078
Title
Automatic image registration based on plain objects detection and recognition in remote sensing tasks
Author
Kazlouski, A. ; Sadykhov, R.K.
Author_Institution
Comput. Syst. Dept., Belarusian State Univ. of Inf. & Radioelecrtronics, Minsk, Belarus
fYear
2014
fDate
23-25 June 2014
Firstpage
218
Lastpage
225
Abstract
Image registration is central problem to many tasks in digital image processing and therefore it has a vast range of applications. A scheme of automatic image registration based on plain objects detection and recognition in remote sensing tasks is presented in this paper. It relates to the concept of plain object in image and includes three subsystems. A subsystem of plain objects detection in image is based on a new method of plain objects detection in image. It relates to the land use classification process, different image segmentation methods and depends on the particular application. A subsystem of conjugate plain objects determination relate to a new method of plain objects recognition in images by shape based on stochastic geometry. It is invariant with respect to projective distortions. A subsystem of image registration determines an optimal geometric transformation and register given input images based on it. This paper reviews existing methods of image registration and emphasizes parametric, non-parametric and hybrid image registration techniques. Experimental results confirm the efficiency of the proposed system.
Keywords
computational geometry; geophysical image processing; image classification; image registration; image segmentation; land use; object detection; object recognition; remote sensing; stochastic processes; automatic image registration; digital image processing; hybrid image registration technique; image segmentation methods; land use classification process; nonparametric image registration technique; optimal geometric transformation; parametric image registration technique; plain object detection; plain object recognition; remote sensing tasks; stochastic geometry; Image recognition; Image registration; Image segmentation; Minimization; Object detection; Pattern recognition; Remote sensing; an arbitrary contour decomposition; hybrid image registration; non-parametric image registration; parametric image registration;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovations in Intelligent Systems and Applications (INISTA) Proceedings, 2014 IEEE International Symposium on
Conference_Location
Alberobello
Print_ISBN
978-1-4799-3019-7
Type
conf
DOI
10.1109/INISTA.2014.6873621
Filename
6873621
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