Block-segment search of local extrema of images based on analysis of brightnesses of related pixels and areas
https://doi.org/10.21122/2309-4923-2019-4-4-9
Abstract
The aim of the work is to develop an algorithm for extracting local extremes of images with low computational complexity and high accuracy. The known algorithms for block search for local extrema have low computational complexity, but only strict maxima and minima are distinguished without errors. The morphological search gives accurate results, highlighting the extreme areas formed by non-severe extremes, however, it has high computational complexity. The paper proposes a block-segment search algorithm for local extremums of images based on an analysis of the brightness of adjacent pixels and regions. The essence of the algorithm is to search for single-pixel local extremes and regions of uniform brightness, comparing the values of their boundary pixels with the values of the corresponding pixels of adjacent regions: the region is a local maximum (minimum) if the values of all its boundary pixels are larger (smaller) or equal to the values of all adjacent pixels. The developed algorithm, as well as the morphological search algorithm, allows detecting all single-pixel local extremes, as well as extreme areas, which exceeds the block search algorithms. At the same time, the developed algorithm in comparison with the morphological search algorithm requires much less time and RAM.
About the Authors
A. T. Nguyen
Belarusian State University of Informatics and Radioelectronics
Belarus
Nguyen Anh Tuan – PG student of department of infocommunication technologies
Belarus
Nguyen Anh Tuan – PG student of department of infocommunication technologies
V. Yu. Tsviatkou
Belarusian State University of Informatics and Radioelectronics
Belarus
V. Yu. Tsviatkou. doctor of Engineering, associate professor, head of department of infocommunications
Belarus
V. Yu. Tsviatkou. doctor of Engineering, associate professor, head of department of infocommunications
References
1. Van Herk, M. A fast algorithm for local minimum and maximum fi on rectangular and octagonal kernels / M. Van Herk // Pattern Recognition Letters. – 1992. – Vol. 13. – P. 517–521.
2. Gil, J. Computing 2-D min, median, and max / J. Gil, M. Werman// IEEE Trans. on PAMI. – 1993. – Vol. 15. – P. 504–507.
3. Coltuc, D. Fast computation of rank order statistics / D. Coltuc, P. Bolon // Proc. Of EUSIPCO. – 2000. – P. 2425– 2428.
4. Neubeck, A. Efficient non-maximum suppression / A. Neubeck, L. Van Gool// Proc. of ICPR. – 2006. – Vol. 3. – P. 850–855.
5. Forstner, W. A fast operator for detection and precise locations of distinct points, corners, and centres of circular features / W. Forstner, E. Gulch // Proc. of Intercommission Conf. on Fast Processing of Photogrammetric Data. – 1987. – P. 281–305.
6. Tuan Q. Pham. Non-maximum Suppression Using fewer than 2 Comparisons per Pixel / Tuan Q. Pham // Advanced Concepts for Intelligent Vision Systems(ACIVS). – 2010. – Vol. 12. – P. 438 –451.
7. Bastys, A. Iris Matching by Local Extremum Points of Multiscale Taylor Expansion / A. Bastys, J. Kranauskas, R. Masiulis // Springer-Verlag Berlin Heidelberg, 2009. ICB 2009, LNCS 5558. – P. 1070–1079.
8. Soille, P. Morphological Image Analysis: Principles and Applications / P. Soille. Springer, 2002. – 391 p
Review
For citations:
Nguyen A.T., Tsviatkou V.Yu. Block-segment search of local extrema of images based on analysis of brightnesses of related pixels and areas. «System analysis and applied information science». 2019;(4):4-9. (In Russ.) https://doi.org/10.21122/2309-4923-2019-4-4-9
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