How Succolarity could be used as another fractal measure in image analysis

Telecommunication Systems

Volumn 52, Issue 3, 2013, Pages 1643-1655

  De Melo, R H C ^a   Conci, A ^a  

^a FLUMINENSE FEDERAL UNIVERSITY   (Brazil)

Author keywords

3D analysis; Binary analysis; Fractal measure; Percolation; Succolarity

Indexed keywords

3D ANALYSIS; BINARY ANALYSIS; DIRECTIONAL INFORMATION; FLOW INFORMATIONS; FRACTAL MEASURES; RECOGNITION PROCESS; SUCCOLARITY; ULTRASOUND IMAGES;

FRACTAL DIMENSION; PATTERN RECOGNITION; PERCOLATION (SOLID STATE); SOLVENTS; TEXTURES;

FINITE DIFFERENCE METHOD;

EID: 84879743437     PISSN: 10184864     EISSN: 15729451     Source Type: Journal    
DOI: 10.1007/s11235-011-9657-3     Document Type: Article

References (22)

1. Mandelbrot, B. B. (1977). Fractal geometry of nature. New York: Freeman.
2. Melo, R. H. C. (2007). Using fractal characteristics such as fractal dimension, Lacunarity and Succolarity to characterize texture patterns on images. Master's thesis, Federal Fluminense University. Link: http://www.ic.uff.br/~rmelo/msc-thesis.htm.
3. Melo, R. H. C.; Vieira, E. A.; Conci, A. (2006). Comparing two approaches to compute Lacunarity of mammograms. In Proceedings of the IEEE signal processing society 13th international conference on systems, signal and image processing and semantic multimodal analysis of digital media (IWSSIP 2006), Budapest, Hungary (pp. 299-302).
4. Melo, R. H. C.; Vieira, E. A.; Conci, A. (2006). Characterizing the Lacunarity of objects and image sets and its use as a technique for the analysis of textural patterns. In J. Blanc-Talon, et al. (Eds.), LNCS: Vol. 4179. Advanced concepts for intelligent vision systems (pp. 208-219). Berlin: Springer.
5. Sarkar, N.; Chaudhuri, B. B. (1992). An efficient approach to estimate Fractal Dimension of textural images. Pattern Recognition, 25, 1035-1041.
6. Block, A.; von Bloh, W.; Schellnhuber, H. J. (1990). Efficient box-counting determination of generalized Fractal Dimensions. Physical Review. A, 42, 1869-1874.
7. Barabási, A. L.; Stanley, H. E. (1995). Fractal concepts in surface growth. New York: Cambridge University Press.
8. Conci, A.; Monteiro, L. H. (2000). Multifractal characterization of texture-based segmentation. In ICIP 2000, Vancouver, Canada (pp. 792-795).
9. Conci, A.; Proença, C. B. (1998). In Computer networks and ISDN Systems, pages: Vol. 30. A fractal image analysis system for fabric inspection based on a box-counting method (pp. 1887-1895). Amsterdam: Elsevier.
10. Mandelbrot, B. B.; Van Ness, J. (1968). Fractional Brownian motion, fractional noise and applications. SIAM Review, 10, 422-437.
11. Barros Filho, M. N. M.; Sobreira, F. A. (2005). Assessing texture pattern in slums across scales: an unsupervised approach. CASA working paper, Centre for Advanced Spatial Analysis, CASA Seminar, University College London, London, 87. Link: http://www.casa.ucl.ac.uk/working-papers/paper87.pdf.
12. Barros Filho, M. N. M.; Sobreira, F. A. (2005). Analysing spatial patterns in slums: a multiscale approach. Congresso Internacional de Planejamento Urbano Regional Integrado e Sustentável, São Carlos (SP). São Carlos: PLURIS.
13. Melo, R. H. C.; Conci, A. (2008). Succolarity: defining a method to calculate this fractal measure. In 15th international conference systems, signals and image processing, 2008. IWSSIP 2008, Bratislava, Slovak Republic (pp. 291-294).
14. Size, G. P.; Duncan, R. K. (2006). Vascular-web. Link: http://www.vascular-web.com, 2006.
15. Batty, M.; Longley, P. (1994). Fractal cities: geometry of form and function (1st ed.). London: Academic Press.
16. Frankhauser, P. (1997). Fractal analysis of urban structures. In E. Holm (Ed.), Modelling space and networks: progress in theoretical and quantitative geography (pp. 145-181). Umea: Gerum Kulturgeografi.
17. Sobreira, F.; Gomes, M. (2001). The geometry of slums: boundaries, packing and diversity. Working paper series, CASA - Centre for Advanced Spatial Analysis - University College London, London, 30. Link: http://www.casa.ucl.ac. uk/working-papers/paper30.pdf.
18. Space Imaging Brazil (2004). Link: http://www.spaceimaging.com.br/.
19. Barros Filho, M. N. M.; Sobreira, F. J. A. (2008). Accuracy of Lacunarity algorithms in texture classification of high spatial resolution images from urban areas. In XXI congress of international society of photogrammetry and remote sensing, 2008, Beijing, China. XXI congress of international society of photogrammetry and remote sensing, Beijing, China.
20. Valous, N. A.; Mendoza, F.; Sun, D.-W.; Allen, P. (2009). Texture appearance characterization of pre-sliced pork ham images using fractal metrics: Fourier analysis dimension and Lacunarity. Food Research International, 42(3), 353-362.
21. Frankhauser, P. (2008). Fractal geometry for measuring and modelling urban patterns. In S. Albeverio, D. Andrey, P. Giordano, & A. Vancheri (Eds.), The dynamics of complex urban systems - an interdisciplinary approach (pp. 241-243). Berlin: Springer.
22. Tannier, C.; Pumain, D. (2005). Fractals in urban geography: a theoretical outline and an empirical example, Cybergeo. European Journal of Geography, 307, 20 http://www.cybergeo.eu/index3275.html, 22 pp.