Segment search for local extremums of images based on the analysis of brightness of adjacent homogeneous areas
Abstract
The problem of finding local extrema on halftone images is considered. Well-known block-search algorithms provide high speed, but they extract only strict (single-pixel) extremes, skipping extreme areas formed by non-strict extremes. Morphological search algorithms provide the selection of non-strict extremes, but have a high computational complexity. A mathematical model and an algorithm based on the brightness analysis of adjacent homogeneous regions are proposed to isolate strict and non-strict local extremes of images with low computational complexity. Their differences from well-known models are: consideration of homogeneous areas, which are formed by non-strict extremes and are local maxima or minima in relation to adjacent areas; elimination of iterative processing of non-extreme pixels; assigning the numbers to local extremes during their search. These differences allowed to increase the accuracy of local extremum extraction in comparison with block search and to reduce the computational complexity in comparison with morphological search.
About the Authors
V. Yu. Tsviatkou
Belarusian State University of Informatics and Radioelectronics
Belarus
Dr. Sci. (Eng.), Assoc. Prof., Head of the Department of Infocommunication Technologies
Belarus
Dr. Sci. (Eng.), Assoc. Prof., Head of the Department of Infocommunication Technologies
Anh Tuan Nguyen
Belarusian State University of Informatics and Radioelectronics
Viet Nam
Postgraduate Student of Department of Infocommunication Technologies
Viet Nam
Postgraduate Student of Department of Infocommunication Technologies
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For citations:
Tsviatkou V.Yu., Nguyen A. Segment search for local extremums of images based on the analysis of brightness of adjacent homogeneous areas. Informatics. 2019;16(3):23-36. (In Russ.)
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