Generalized projective morphology
  Y.V. Vizilter
State Research Institute  of Aviation Systems
Full text of article: Russian language.
Abstract:
The description of  proposed generalized projective morphology is given. Algebraic basis of  projective morphology is considered. Formal and criteria-based schemes for  morphology design are described. Some sufficient conditions of projectiveness  for criteria-based morphological operators are proved. Projectors are proposed  and explored based on: minimal distance (maximal similarity) criterion, maximal  norm of projection, predicate-type criterions, feature vectors, parametric  models and dynamic programming procedures. The class of criteria-based morphologies  based on structural interpolation operators is proposed.
Key words:
Mathematical Morphology,  Image Processing, Image Analysis.
Citation: Vizilter YuV. Generalized Projective Morphology. Computer  Optics 2008; 32(4): 384-99.
References:
  - Vizilter YuV, Zheltov SYu.  Comparison and localization of image elements using projective morphology [In  Russian].  Vestnik Komp'iuternykh i  Informatsionnykh Tekhnologii (Herald of Computer and Information Technologies)  2008; 2: 14-22. 
- Pavel M. Fundamentals of Pattern  Recognition. Marcel Dekker. Inc. New York 1989. 
- Serra J. Image Analysis and  Mathematical Morphology. Academic Press, London 1982. 
- Pytiev YuP. Morphological image  analysis [In Russian]. Doklady AN SSSR (Proceedings of the Academy of Sciences  of the USSR) 1983; 269(5): 1061-1064. 
- Bratko I. Prolog programming for  artificial intelligence [In Russian]. Moscow: “Mir” Publisher 1990; 560 p. 
- Hogger K. Introduction to logic  programming [In Russian]. Moscow: “Mir” Publisher 1988; 348 p. 
- Berge V. Methods of recursive  programming [In Russian]. Moscow: “Mashinostroenie” (Mechanical Engineering)  Publisher 1983; 248 p. 
- Werner T. A Linear Programming  Approach to Max-sum problem: A Review. Research reports of CMP. Czech Technical  University in Prague 2005; 25: 46. 
- Geman S, Geman D. Stochastic  relaxation, Gibbs distributions, the Bayesian restoration of images. IEEE  Trans. Pattern Analysis, Machine Intelligence 1984; 6: 721-741. 
- Forsyth D, Ponce J. Computer vision:  a modern approach [In Russian]. Moscow: “Williams” Publisher 2004; 928 p. 
- Mottl V, Blinov A, Kopylov A, Kostin  A. Optimization techniques on pixel neighborhood graphs for image processing.  Graph-Based Representations in Pattern Recognition. J.-M. Jolion and W.G.  Kropatsch, ed. Computing, Supplement 12. Springer-Verlag/Wien 1998: 135-145. 
-   Yeong-Chyang Shih F, Mitchell O.R. Threshold  Decomposition of gray Scale Morphology into Binary Morphology. IEEE trans. on  pattern analysis, machine intelligence.   January 1989; II(1).
  
  
  
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