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Multiscale estimation of multiple orientations based on morphological directional openings

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Abstract

This paper introduces a novel approach to estimate multiple orientations at each pixel of a gray image at different scales. The main orientations are provided by a bank of directional openings. Gathering the responses of the filtered directional openings provide at each pixel a discrete sequence which is the directional signature. Then, the directional signature is interpolated by cubic B-splines, and the multiple orientations at each pixel are obtained by means of peak detection in the continuous directional signature. This procedure is performed using structuring elements with different lengths which results in a multiscale approach. The comparison with other existing methods as well as the experimental results on images shows the ability of the proposed method to detect multiple orientations in textured images at different scales with high accuracy.

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References

  1. Akl, A., Yaacoub, C., Donias, M., Da Costa, J.P., Germain, C.: Synthesis of arbitrary-shaped textures constrained by the structure tensor field. Signal Image Video Process. 12, 41–49 (2017)

    Article  Google Scholar 

  2. Bigün, J., Granlund, G., Wiklund, J.: Multidimensional orientation estimation with applications to texture analysis and optical flow. IEEE Trans. Pattern Anal. Mach. Intell. 13(8), 775–790 (1991)

    Article  Google Scholar 

  3. Lee, J.C., Lo, T.M., Chang, C.P.: Dorsal hand vein recognition based on directional filter bank. Signal Image Video Process. 10(1), 145–152 (2016)

    Article  Google Scholar 

  4. Muhlich, M., Dahmen, T., Aach, T.: Design of multi-steerable filters and their application for the detection of corners and junctions. In: IEEE international confererence on image processing, vol. 4, pp. 33–36 (2007)

  5. Peker, M., Karakaya, F.: SIH: segmented intensity histogram for orientation estimation in image matching. Signal Image Video Process. 10(6), 1135–1142 (2016)

    Article  Google Scholar 

  6. Zahedi, M., Ghadi, O.R.: Combining Gabor filter and FFT for fingerprint enhancement based on a regional adaption method and automatic segmentation. Signal Image Video Process. 9(2), 267–275 (2015)

    Article  Google Scholar 

  7. Farneback, G.: Fast and accurate motion estimation using orientation tensors and parametric motion models. In: Proceedings of the 15th international conference on pattern recognition, vol. 1, pp. 135–139 (2000)

  8. Larrey-Ruiz, J., Verdú-Monedero, R., Morales-Sánchez, J., Angulo, J.: Frequency domain regularization of d-dimensional structure tensor-based directional fields. Image Vis. Comput. 29(9), 620–630 (2011)

    Article  Google Scholar 

  9. Fortun, D., Bouthemy, P., Kervrann, C.: Optical flow modeling and computation: a survey. Comput. Vis. Image Underst. 134, 1–21 (2015)

    Article  MATH  Google Scholar 

  10. Stache, N.C., Stehle, T.H., Mühlich, M., Aach, T.: Towards multiple-orientation based tensor invariants for object tracking. In: European signal processing conference EURASIP (2006)

  11. Bekkers, E., Duits, R., Berendschot, T., ter Haar Romeny, B.: A multi-orientation analysis approach to retinal vessel tracking. J. Math. Imaging Vis. 49(3), 583–610 (2014)

    Article  MATH  Google Scholar 

  12. Guo, X., Li, Q., Sun, C.: Automatic localization of optic disk based on texture orientation voting. Signal Image Video Process. 11, 1115–1122 (2017)

    Article  Google Scholar 

  13. Schneider, M., Hirsch, S., Weber, B., Székely, G., Menze, B.H.: Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters. Med. Image Anal. 19(1), 220–249 (2015)

    Article  Google Scholar 

  14. Strisciuglio, N., Azzopardi, G., Vento, M., Petkov, N.: Multiscale blood vessel delineation using B-COSFIRE filters. Lect. Notes Comput. Sci. 9257, 300–312 (2015)

    Article  MathSciNet  Google Scholar 

  15. Zhang, J., Bekkers, E., Abbasi, S., Dashtbozorg, B., ter Haar Romeny, B.: Robust and fast vessel segmentation via gaussian derivatives in orientation scores. Lect. Notes Comput. Sci. 9279, 537–547 (2015)

    Article  MathSciNet  Google Scholar 

  16. Knutsson, H.: Representing local structure using tensors. In: Proceedings of the 6th Scandinavian conference of image analysis, pp. 244–251 (1989)

  17. Mühlich, M., Aach, T.: Analysis of multiple orientations. IEEE Trans. Image Process. 18(7), 1424–1437 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  18. Knutsson, H., Granlund, G.H.: Texture analysis using two-dimensional quadrature filters. IEEE computer society workshop on computer architecture for pattern analysis and image database management (1983)

  19. Perona, P.: Deformable kernels for early vision. IEEE Trans. Pattern Anal. Mach. Intell. 17, 488–499 (1991)

    Article  Google Scholar 

  20. Bigün, J., du Buf, J.M.H.: N-folded symmetries by complex moments in Gabor space and their application to unsupervised texture segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 16(1), 80–87 (1994)

    Article  Google Scholar 

  21. Khan, M.A.U., Khan, T.M.: Calibrating second-moment matrix for better shape adaptation with bias term from directional filter bank. Signal Image Video Process. 11, 1453–1460 (2017)

    Article  Google Scholar 

  22. Freeman, W., Adelson, E.: The design and use of steerable filters. IEEE Trans. Pattern Anal. Mach. Intell. 13(9), 891–906 (1991)

    Article  Google Scholar 

  23. Simoncelli, E.P., Farid, H.: Steerable wedge filters for local orientation analysis. IEEE Trans. Image Process. 5(9), 1377–1382 (1996)

    Article  Google Scholar 

  24. Mühlich, M., Friedrich, D., Aach, T.: Design and implementation of multisteerable matched filters. IEEE Trans. Pattern Anal. Mach. Intell. 34(2), 279–291 (2012)

    Article  Google Scholar 

  25. Pouliquen, F., Germain, C., Baylou, P.: Line orientation operator. In: Proceedings of the IEEE international conference on image processing (2001)

  26. Michelet, F., Costa, J.P.D., Lavialle, O., Berthoumieu, Y., Baylou, P., Germain, C.: Estimating local multiple orientations. Signal Process. 87(7), 1655–1669 (2007)

    Article  MATH  Google Scholar 

  27. Zhang, W.C., Shui, P.L.: Contour-based corner detection via angle difference of principal directions of anisotropic gaussian directional derivatives. Pattern Recognit. 48(9), 2785–2797 (2015)

    Article  Google Scholar 

  28. Soille, P.: Morphological Image Analysis. Springer, Berlin (1999)

    Book  MATH  Google Scholar 

  29. Akagunduz, E.: Shape recognition using orientational and morphological scale-spaces of curvatures. IET Comput. Vis. 9, 750–757 (2015)

    Article  Google Scholar 

  30. Jalba, A., Wilkinson, M., Roerdink, J.: Shape representation and recognition through morphological curvature scale spaces. IEEE Trans. Image Process. 15(2), 331–341 (2006)

    Article  Google Scholar 

  31. Sigurdsson, E.M., Valero, S., Benediktsson, J.A., Chanussot, J., Talbot, H., Stefánsson, E.: Automatic retinal vessel extraction based on directional mathematical morphology and fuzzy classification. Pattern Recognit. Lett. 47, 164–171 (2014)

    Article  Google Scholar 

  32. Merveille, O., Talbot, H., Najman, L., Passat, N.: Ranking orientation responses of path operators: motivations, choices and algorithmics. Lecture notes in computer science, vol. 9082 (2015)

  33. Angulo, J., Verdú-Monedero, R., Morales-Sánchez, J.: Multiscale local multiple orientation estimation using mathematical morphology and B-spline interpolation. In: Proceedings of 7th international symposium on image and signal processing and analysis (2011)

  34. Legaz-Aparicio, A., Verdú-Monedero, R., Morales-Sánchez, J., Larrey-Ruiz, J., Angulo, J.: Detection of retinal vessel bifurcations by means of multiple orientation estimation based on regularized morphological openings. In: XIII Mediterranean conference on medical and biological engineering and computing (2013)

  35. Soille, P., Talbot, H.: Directional morphological filtering. IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1313–1329 (2001)

    Article  Google Scholar 

  36. Morales, S., Legaz-Aparicio, A.G., Naranjo, V., Verdú-Monedero, R.: Determination of bifurcation angles of the retinal vascular tree through multiple orientation estimation based on regularized morphological openings. In: International conference on bio-inspired systems and signal processing (2015)

  37. Basu, M.: Gaussian-based edge-detection methods-a survey. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 32(3), 252–260 (2002)

    Article  Google Scholar 

  38. Lopez-Molina, C., Galar, M., Bustince, H., De Baets, B.: On the impact of anisotropic diffusion on edge detection. Pattern Recognit. 47(1), 270–281 (2014)

    Article  Google Scholar 

  39. Duits, R., Duits, M., van Almsick, M., ter Haar Romeny, B.: Invertible orientation scores as an application of generalized wavelet theory. Pattern Recognit. Image Anal. 17(1), 42–75 (2007)

    Article  Google Scholar 

  40. Thévenaz, P., Blu, T., Unser, M.: Interpolation revisited. IEEE Trans. Med. Imaging 19(7), 739–758 (2000)

    Article  Google Scholar 

  41. Verdú-Monedero, R., Angulo, J., Serra, J.: Anisotropic morphological filters with spatially-variant structuring elements based on image-dependent gradient fields. IEEE Trans. Image Process. 20(1), 200–212 (2011)

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Rafael Verdú-Monedero.

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Legaz-Aparicio, ÁG., Verdú-Monedero, R. & Angulo, J. Multiscale estimation of multiple orientations based on morphological directional openings. SIViP 12, 1245–1253 (2018). https://doi.org/10.1007/s11760-018-1276-y

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  • DOI: https://doi.org/10.1007/s11760-018-1276-y

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