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Sensors  2013 

3D Image Acquisition System Based on Shape from Focus Technique

DOI: 10.3390/s130405040

Keywords: 3D image acquisition system, shape from focus, focus measure, agronomic scenes

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Abstract:

This paper describes the design of a 3D image acquisition system dedicated to natural complex scenes composed of randomly distributed objects with spatial discontinuities. In agronomic sciences, the 3D acquisition of natural scene is difficult due to the complex nature of the scenes. Our system is based on the Shape from Focus technique initially used in the microscopic domain. We propose to adapt this technique to the macroscopic domain and we detail the system as well as the image processing used to perform such technique. The Shape from Focus technique is a monocular and passive 3D acquisition method that resolves the occlusion problem affecting the multi-cameras systems. Indeed, this problem occurs frequently in natural complex scenes like agronomic scenes. The depth information is obtained by acting on optical parameters and mainly the depth of field. A focus measure is applied on a 2D image stack previously acquired by the system. When this focus measure is performed, we can create the depth map of the scene.

References

[1]  Barnard, S.; Fischler, M. Computational stereo. ACM Comput. Surv. (CSUR) 1982, 14, 553–572.
[2]  Faugeras, O. Three-Dimensional Computer Vision: A Geometric Viewpoint; The MIT Press: Cambridge, MA USA, 1993.
[3]  Hartley, R. Multiple View Geometry in Computer Vision; Cambridge University Press: Cambridge, UK, 2008.
[4]  Zhang, R.; Tsai, P.; Cryer, J.; Shah, M. Shape-from-shading: A survey. IEEE Trans. Patt. Anal. Mach. Intell. 1999, 21, 690–706.
[5]  Nayar, S.K.; Nakagawa, Y. Shape from Focus; Carnegie Mellon University: Pittsburgh, PA, USA, 1989.
[6]  Willson, R.; Shafer, S. Dynamic Lens Compensation for Active Color Imaging and Constant Magnification Focusing. Technical Report CMU-RI-TR-91-26; Carnegie Mellon University: Pittsburgh, PA, USA, 1991.
[7]  Nayar, S.K.; Nakagawa, Y. Shape from Focus. IEEE Trans. Patt. Anal. Mach. Intell. 1994, 16, 824–831.
[8]  Complete Camera Calibration Toolbox for Matlab. Available online: http://www.vision.caltech.edu/bouguetj (accessed on 15 April 2013).
[9]  Watanabe, M.; Nayar, S. Telecentric optics for focus analysis. IEEE Trans. Patt. Anal. Mach. Intell. 1997, 19, 1360–1365.
[10]  Kuglin, C.D.; Hines, D.C. The Phase Correlation Image Alignment Method. Proceedings of the IEEE Conference on Cybernetics and Society, San Francisco, CA, USA, 23–25 September 1975.
[11]  Raj, A.; Staunton, R. Estimation of Image Magnification Using Phase Correlation. Proceedings of the IEEE International Conference on Computational Intelligence and Multimedia Applications, Sivakasi, India, 13–15 December 2007; pp. 490–494.
[12]  Brenner, J.; Dew, B.; Horton, J.; King, T.; Neurath, P.; Selles, W. An automated microscope for cytologic research a preliminary evaluation. J. Histochem. Cytochem. 1976, 24, 100.
[13]  Subbarao, M.; Choi, T.; Nikzad, A. Focusing techniques. Opt. Eng. 1993, 32, 2824–2836.
[14]  Tenenbaum, J. Accommodation in Computer Vision. Ph.D. Thesis, Stanford University, Stanford, CA, USA, 1970.
[15]  Xu, X.; Wang, Y.; Tang, J.; Zhang, X.; Liu, X. Robust automatic focus algorithm for low contrast images using a new contrast measure. Sensors 2011, 11, 8281–8294.
[16]  Groen, F.; Young, I.; Ligthart, G. A comparison of different focus functions for use in autofocus algorithms. Cytometry 1985, 6, 81–91.
[17]  Firestone, L.; Cook, K.; Culp, K.; Talsania, N.; Preston, K., Jr. Comparison of autofocus methods for automated microscopy. Cytometry 1991, 12, 195–206.
[18]  Malik, A.; Choi, T. A novel algorithm for estimation of depth map using image focus for 3D shape recovery in the presence of noise. Patt. Recog. 2008, 41, 2200–2225.
[19]  Shen, C.; Chen, H. Robust Focus Measure for Low-Contrast Images. Proceedings of the IEEE International Conference on Consumer Electronics, Las Vegas, NV, USA, 7–11 January 2006; pp. 69–70.
[20]  Xie, H.; Rong, W.; Sun, L. Wavelet-Based Focus Measure and 3-D Surface Reconstruction Method for Microscopy Images. Proceedings of the IEEE /RSJ International Conference on Intelligent Robots and Systems, Beijing, China, 9–15 October 2006; pp. 229–234.
[21]  Mahmood, M.; Choi, W.; Choi, T. PCA-based method for 3D shape recovery of microscopic objects from image focus using discrete cosine transform. Microsc. Res. Tech. 2008, 71, 897–907.
[22]  Pech-Pacheco, J.; Cristobal, G.; Chamorro-Martinez, J.; Fernandez-Valdivia, J. Diatom Autofocusing in Brightfield Microscopy: A Comparative Study. Proceedings of the 15th International Conference on Pattern Recognition, Barcelona, Spain, 3–7 September 2000.
[23]  Xu, X.; Wang, Y.; Zhang, X.; Li, S.; Liu, X.; Wang, X.; Tang, J. A comparison of contrast measurements in passive autofocus systems for low contrast images. Multimed. Tools Appl. 2012, doi:10.1007/s11042-012-1194-x.
[24]  Cointault, F.; Guérin, D.; Guillemin, J.; Chopinet, B. In-field wheat ears counting using colour-texture image analysis. N. Z. J. Crop Hort. Sci. 2008, 36, 117–130.

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