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Mathematical Problems of Computer Science 28, 2007, 88 – 93. 

 
88 
 

 
 

Technique for Coherent Segmentation 
of Image and Applications 

 
David G. Asatryan1, Grigor S. Sazhumyan2, Hayk S. Shahverdyan3 

 
1,2

Institute for Informatics and Automation Problems of NAS of RA 
3
State Engineering University of Armenia 

 
 

Abstract 
 

In this paper we describe a software tool created according to an algorithm, 
which was proposed earlier by authors for coherent and multi-scale segmentation of 
an image. The algorithm is based on the finding of all connected segments, the pixels 
of which belong to the same, determined beforehand and adjustable levels of 
intensity. Various modes of operation of the software are described, which allows to 
separate segments or to carry out full segmentation, as well as to transfer the 
parameters of one segment to others and to estimate quality of the carried out 
segmentation. It is shown that the segmentation procedure is able to determine 
simultaneously edges and contours in the image. The results of the computing 
experiments showing efficiency of developed system are given.  

 

 
 References 
 

[1] W.Pratt. Digital Image Processing. 3-rd ed., J.Wiley & Sons, Inc., N.Y., 2001. 
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Englewood Cliffs, NJ, 2002. 
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Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, 1986. 
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Extension Technique”. Proc. of XII Int. Conf. on Symmetry Methods in Physics. 
Yerevan, 2006, 10p. (To be printed).  

[6] Д.Асатрян, Г. Сажумян. “Об одном методе пороговой локальной сегментации 
изображения”. Mathematical Problems of Computer Science, IIAP, Yerevan, Armenia, 
26, 2006, pp. 15-20. 

[7] Г. Сажумян. “Программная система для пороговой сегментации изображения”. 
Материалы годичной конференции ГИУА, 2006 г., 4 стр. 

[8] Д. Асатрян, Г. Сажумян. “Метод когерентной сегментации и его приложение к 
восстановлению поврежденных изображений”. Вестник ГИУА, сер. Моделирование, 
оптимизация, управление, вып. 9, т. 2, 2006 г., с. 15-21. 
[9] http://www.berkeley.edu 
[10] P. Arbel´aez and L. Cohen. Energy partitions and image segmentation. Technical 
report, CEREMADE, 2003. 



D. G. Asatryan, G. S. Sazhumyan, H. S. Shahverdyan 
 

89 
[11] J. Melonakos, R. Al-hakim,, J. Fallon, A. Tannenbaum. “Knowledge-based 
segmentation of brain MRI scans using the insight toolkit”. Insight Journal, 2005, 
http://hdl.handle.net/1926/44. 

 
 
 

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