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Journal of applied research and technology

versão On-line ISSN 2448-6736versão impressa ISSN 1665-6423

J. appl. res. technol vol.8 no.3 Ciudad de México Dez. 2010

 

Computation of the Euler Number of a Binary Image Composed of Hexagonal Cells

 

J. H. Sossa–Azuela*1, E. V. Cuevas–Jiménez2, D. Zaldivar–Navarro2

 

1 Centro de Investigación en Computación–IPN, Av. Juan de Dios Bátiz, esquina con Miguel Othón de Mendizábal, Mexico City, C. P. 07738. MEXICO *E–mail: hsossa@cic.ipn.mx

2 Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara Av. Revolución 1500 Col. Olímpica C.P. 44430 Guadalajara, Jal, MEXICO.

 

ABSTRACT

Most of the proposals to compute the Euler number of a binary image have been designed to work with images composed of squared cells. Only a few of these methods (in the case of images composed of hexagonal cells) have been reported in literature, although it is known that images composed of hexagonal cells do not suffer from the problems of connectivity frequently found in the case of images composed of squared cells. In this paper, a new way to compute the Euler number (E) of a binary image composed of hexagonal cells is presented. For this, the perimeter P of the isolated regions in the image, their contact perimeter Pc and the type T of a cell are used to obtain this important invariant. The proposal can be used alone or in combination with other features to describe any binary planar shape composed of hexagonal pixels for its further recognition.

Keywords: Binary image characterization, Perimeter, Contact Perimeter, Euler number or genus, Topological descriptor, Topological invariant.

 

RESUMEN

El principal objetivo de este trabajo es el presentar una nueva clase de controlador de tipo retroalimentado, el cual contiene en su estructura una forma polinomial del llamado error de control, el controlador propuesto es aplicado a un quimiostato sulfato–reductor, el cual pudiera ser usado para varios fines biotecnológicos, como la remoción de metales pesados en aguas residuales. El comportamiento a lazo cerrado del quimiostato considerado es teóricamente analizado y se prueba convergencia práctica a la trayectoria óptima seleccionada. La metodología propuesta es aplicada a un modelo cinético de una bacteria sulfato–reductora experimentalmente validado y experimentos numéricos complementarios muestran un comportamiento a lazo cerrado satisfactorio en comparación con otros controladores.

 

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References

[1] X. He and W. Jia (2005). Hexagonal Structure for Intelligent Vision, Information and Communication Technologies, ICICT, pp. 52– 64.         [ Links ]

[2] R. C. Staunton (1989). The design of hexagonal sampling structures for image digitization and their use with local operators, Image Vision Computing, 7(3):162–166.         [ Links ]

[3] L. Middleton and J. Sivaswamy (2005). Hexagonal Image Processing; A Practical Approach, Springer.         [ Links ]

[4] L. Middleton and J. Sivaswamy (2001). Edge Detection in a Hexagonal–Image Processing Framework. Image and Vision Computing 19:1071–1081.         [ Links ]

[5] A. Rosenfeld and A. C. Kak (1982). Digital Picture Processing, Academic Press Inc. New York.         [ Links ]

[6] R. C. Gonzalez and R. E. Woods (1993). Digital Image Processing, Addison–Wesley, Reading, Massachussets.         [ Links ]

[7] S. D. Zenzo, L. Cinque and S. Levivaldi (1996). Run–based algorithms for binary image analysis and processing, IEEE Transactions on PAMI, 18(1):83–89.         [ Links ]

[8] H. S. Yang and S. Sengupta (1988). Intelligent shape recognition for complex industrial tasks, IEEE Control Systems Magazine 8(3):23–29.         [ Links ]

[9] L. Snidaro and G. L. Foresti (2003). Real–time Thresholding with Euler Numbers. Pattern Recognition Letters 24(9–10):1533–1544.         [ Links ]

[10] J. Athow, N. Abbasi and A. Amer (2009). A Real–Time FPGA Architecture of a Modified Stable Euler–Number Algorithm for Image Binarization. Technical Report 2009–1–ATHOW Department of Electrical and Computer Engineering, Concordia University. January 2009.         [ Links ]

[11] M. Vatsa, R, Singh, P. Mitra and A. Noore (2004). Signature Verification using Static and Dynamic Features (2004). ICONIP 2004. LNCS 3316. Springer–Verlag, Pp. 350–355.         [ Links ]

[12] Ch. Zhang, Z. Qiu and D. Sun and J. Wu (2006). Euclidean Quality Assessment for Binary Images. 18th International Conference on Pattern Recognition, ICPR 2006. Pp. 300–303.         [ Links ]

[13] L. P. Wong and H. T. Ewe (2007). A Sutdy of Nodule Detection using Opaque Object Filter. Biomed 06. IFMBE Proceedings 15. Pp. 236–240. Springer Verlag.         [ Links ]

[14] S. Dey, B.B. Bhattacharya, M.K. Kundu, T. Acharya (2000). A fast algorithm for computing the Euler number of an image and its VLSI implementation, in Proc. 13th International Conference on VLSI Design, pp. 330–335.         [ Links ]

[15] A. Bishnu, B. B. Bhattacharya, M. K. Kundu, C.A. Murthy, T. Acharya (2005). A pipeline architecture for computing the Euler number of a binary image. Journal of Systems Architecture 51(8):47–487.         [ Links ]

[16] A. Bishnu, B. B. Bhattacharya, M. K. Kundu, C.A. Murthy, T. Acharya (2001). On chip computation of Euler number of a binary image for efficient database search, Proc. of the International Conference on Image Processing (ICIP), Vol. III, pp. 310–313.         [ Links ]

[17] T. Acharya, B. B. Bhattacharya, A. Bishnu, M. K. Kundu, Ch. A. Murthy (2006). Computing the Euler Number of a Binary Image. United States Patent 7027649 B1. April 11, 2006.

[18] Ch. R. Dyer (1980). Computing the Euler number of an image from its quatree. Comput. Vision, Graphics Image Process. 13, 270–276.         [ Links ]

[19] H. Samet et al. (1985). Computing Geometric Properties of Images Represented by Linear Quadtrees. IEEE Trans. PAMI, 7(2):229–240.         [ Links ]

[20] H. Beri (1987). Computing the Euler characteristic and related additive functionals of digital objects from their beentree representation, Comput. Vision, Graphics Image Process. 40, 115–126.         [ Links ]

[21] H. Beri and W. Nef (1984). Algorithms for the Euler characteristic and related additive functionals of digital objects, Comput. Vision, Graphics Image Process. 28, 166–175.         [ Links ]

[22] M. H. Chen and P. F. Yan (1988). A fast algorithm to calculate the Euler number for binary images, Pattern Recognition Letters 8(12):295–297.         [ Links ]

[23] F. Chiavetta and V. Di Gesú (1993). Parallel computation of the Euler number via connectivity graph, Pattern Recognition Letters 14(11):849–859.         [ Links ]

[24] W. Nagel, J. Ohser and K. Pischang (2000). An integral–geometric approach for the Euler–Poincare characteristic of spatial images. Journal of Microsc, 189:54–62.         [ Links ]

[25] LIN Xiaozhu, SHA Yun, JI Junwei & WANG Yanmin (2006). A proof of image Euler Number formula. Science in China: Series F Information Sciences 49(3):364–371.         [ Links ]

[26] J. L. Díaz de León S. and H. Sossa (1996). On the computation of the Euler number of a binary object. Pattern Recognition, 29(3):471–476.         [ Links ]

[27] J. Serra (1982). Image Analysis and Mathematical Morphology, Academic Press.         [ Links ]

[28] E. Bribiesca (1997). Measuring 2–D shape compactness using the contact perimeter, Computers Math. Applic. 33(11):1–9.         [ Links ]

 

Acknowledgments

The authors wish to thank SIP–IPN for the economical support under grant number 20100468. The authors also thank the European Union, the European Commission and CONACYT for their economical support. This paper has been prepared by economical support of the European Commission under grant FONCICYT 93829. The content of this paper is an exclusive responsibility of the IPN and the UDEG and it cannot be considered to reflect the position of the European Union. We also thank the reviewers for their comments to improve this paper.

 

Annex

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