Evaluating color texture descriptors under large variations of controlled lighting conditions

Journal of the Optical Society of America A: Optics and Image Science, and Vision

Volumn 33, Issue 1, 2016, Pages 17-30

  Cusano, Claudio ^a   Napoletano, Paolo ^b   Schettini, Raimondo ^b  

^a UNIVERSITY OF PAVIA   (Italy)

^b UNIVERSITY OF MILANO BICOCCA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

LIGHTING;

COLOR NORMALIZATION; COLOR TEXTURES; IMAGING CONDITIONS; LIGHTING CONDITIONS; STATISTICAL DESCRIPTORS; TEXTURE DESCRIPTORS; TEXTURE FEATURES; VARYING LIGHTING;

COLOR;

EID: 84962431653     PISSN: 10847529     EISSN: 15208532     Source Type: Journal    
DOI: 10.1364/JOSAA.33.000017     Document Type: Article

References (63)

1. A. Drimbarean and P. Whelan, "Experiments in colour texture analysis", Pattern Recogn. Lett. 22, 1161-1167 (2001).
2. T. Mäenpää and M. Pietikäinen, "Classification with color and texture: jointly or separately?" Pattern Recogn. 37, 1629-1640 (2004).
3. F. Bianconi, R. Harvey, P. Southam, and A. Fernández, "Theoretical and experimental comparison of different approaches for color texture classification", J. Electron. Imaging 20, 043006 (2011).
4. Y. LeCun, Y. Bengio, and G. Hinton, "Deep learning", Nature 521, 436-444 (2015).
5. M. Cimpoi, S. Maji, and A. Vedaldi, "Deep filter banks for texture recognition and segmentation", in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015), pp. 3828-3836.
6. S. Hossain and S. Serikawa, "Texture databases-a comprehensive survey", Pattern Recogn. Lett. 34, 2007-2022 (2013).
7. F. Bianconi and A. Fernández, "An appendix to "texture databases-a comprehensive survey", Pattern Recogn. Lett. 45, 33-38 (2014).
8. M. Cimpoi, S. Maji, I. Kokkinos, S. Mohamed, and A. Vedaldi, "Describing textures in the wild", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2014), pp. 3606-3613.
9. "RawFooT DB: Raw Food Texture Database", http://projects.ivl.disco.unimib.it/rawfoot/(2015).
10. S. Bell, P. Upchurch, N. Snavely, and K. Bala, "Material recognition in the wild with the materials in context database", arXiv:1412.0623 (2014).
11. L. Sharan, C. Liu, R. Rosenholtz, and E. H. Adelson, "Recognizing materials using perceptually inspired features", Int. J. Comput. Vis. 103, 348-371 (2013).
12. P. Brodatz, Textures: a Photographic Album for Artists and Designers (Dover, 1966), Vol. 66.
13. K. Dana, B. Van-Ginneken, S. Nayar, and J. Koenderink, "Reflectance and texture of real world surfaces", ACM Trans. Graph. 18, 1-34 (1999).
14. Media Laboratory at Heriot-Watt University, "Vistex database", http://vismod.media.mit.edu/vismod/imagery/VisionTexture.
15. G. Smith, "Meastex image texture database and test suite", http://www.texturesynthesis.com/meastex/meastex.html.
16. Texturelab Edinburgh at Massachusetts Institute of Technology, "Photex database", http://www.macs.hw.ac.uk/texturelab/resources/databases/photex/.
17. T. Ojala, T. Maenpaa, M. Pietikainen, J. Viertola, J. Kyllonen, and S. Huovinen, "Outex-new framework for empirical evaluation of texture analysis algorithms", in Proceedings of 16th International Conference on Pattern Recognition (IEEE, 2002), Vol. 1, pp. 701-706.
18. R. Péteri, S. Fazekas, and M. J. Huiskes, "Dyntex: A comprehensive database of dynamic textures", Pattern Recogn. Lett. 31, 1627-1632 (2010).
19. S. Lazebnik, C. Schmid, and J. Ponce, "A sparse texture representation using local affine regions", IEEE Trans. Pattern Anal. Mach. Intell. 27, 1265-1278 (2005).
20. B. Caputo, E. Hayman, and P. Mallikarjuna, "Class-specific material categorization", in 10th IEEE International Conference on Computer Vision (IEEE, 2005), Vol. 2, pp. 1597-1604.
21. G. J. Burghouts and J.-M. Geusebroek, "Material-specific adaptation of color invariant features", Pattern Recogn. Lett. 30, 306-313 (2009).
22. A. Fernández, O. Ghita, E. González, F. Bianconi, and P. F. Whelan, "Evaluation of robustness against rotation of LBP, CCR and ILBP features in granite texture classification", Mach. Vis. Appl. 22, 913-926 (2011).
23. R. Kwitt and P. Meerwald, "Stex: Salzburg texture image database", http://www.wavelab.at/sources/STex/.
24. G. Kylberg, "Automatic virus identification using TEM: image segmentation and texture analysis", Ph. D. thesis (Acta Universitatis Upsaliensis, 2014).
25. A. R. Backes, D. Casanova, and O. M. Bruno, "Color texture analysis based on fractal descriptors", Pattern Recogn. 45, 1984-1992 (2012).
26. A. Poirson and B. Wandell, "Pattern-color separable pathways predict sensitivity to simple colored patterns", Vis. Res. 36, 515-526 (1996).
27. R. Khan, J. Van De Weijer, D. Karatzas, and D. Muselet, "Towards multispectral data acquisition with hand-held devices", in International Conference on Image Processing (2013), pp. 2053-2057.
28. G. Wyszecki and W. S. Stiles, Color Science (Wiley, 1982), Vol. 8.
29. M. Mirmehdi, X. Xie, and J. Suri, Handbook of Texture Analysis (Imperial College, 2009).
30. F. Bianconi and A. Fernández, "Evaluation of the effects of Gabor filter parameters on texture classification", Pattern Recogn. 40, 3325-3335 (2007).
31. R. Haralick, "Statistical and structural approaches to texture", Proc. IEEE 67, 786-804 (1979).
32. T. Ojala, M. Pietikäinen, and T. Mänepää, "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns", IEEE Trans. Pattern Anal. Mach. Intell. 24, 971-987 (2002).
33. G. Sharma, S. Ul Hussain, and F. Jurie, "Local Higher-Order Statistics (lhs) for Texture Categorization and Facial Analysis", in Lecture Notes in Computer Science (Springer, 2012), Vol. 7578, pp. 1-12.
34. A. S. Razavian, H. Azizpour, J. Sullivan, and S. Carlsson, "CNN features off-the-shelf: an astounding baseline for recognition", in IEEE Conference on Computer Vision and Pattern Recognition Workshops (2014), pp. 512-519.
35. R. Khan, D. Muselet, and A. Trémeau, "Classical texture features and illumination color variations", in Proceedings of third International Conference on Machine Vision (2010), pp. 280-285.
36. G. Finlayson, S. Hordley, G. Schaefer, and G. Yun Tian, "Illuminant and device invariant colour using histogram equalisation", Pattern Recogn. 38, 179-190 (2005).
37. M. Seifi, X. Song, D. Muselet, and A. Tremeau, "Color texture classification across illumination changes", in Conference on Colour in Graphics, Imaging, and Vision (2010), pp. 332-337.
38. C. Cusano, P. Napoletano, and R. Schettini, "Combining local binary patterns and local color contrast for texture classification under varying illumination", J. Opt. Soc. Am. A 31, 1453-1461 (2014).
39. O. Drbohlav and A. Leonardis, "Towards correct and informative evaluation methodology for texture classification under varying viewpoint and illumination", Comput. Vis. Image Underst. 114, 439-449 (2010).
40. U. Kandaswamy, S. A. Schuckers, and D. Adjeroh, "Comparison of texture analysis schemes under nonideal conditions", IEEE Trans. Image Process. 20, 2260-2275 (2011).
41. M. Pietikainen, S. Nieminen, E. Marszalec, and T. Ojala, "Accurate color discrimination with classification based on feature distributions", in Proceedings of the 13th International Conference on Pattern Recognition (1996), Vol. 3, pp. 833-838.
42. G. Paschos, "Fast color texture recognition using chromaticity moments", Pattern Recogn. Lett. 21, 837-841 (2000).
43. V. Arvis, C. Debain, M. Berducat, and A. Benassi, "Generalization of the co-occurrence matrix for colour images: application to colour texture", Image Anal. Stereol. 23, 63-72 (2004).
44. M. Hauta-Kasari, J. Parkkinen, T. Jaaskelainen, and R. Lenz, "Generalized co-occurrence matrix for multispectral texture analysis", in Proceedings of the 13th International Conference on Pattern Recognition (1996), Vol. 2, pp. 785-789.
45. A. Jain and G. Healey, "A multiscale representation including opponent color features for texture recognition", IEEE Trans. Image Process. 7, 124-128 (1998).
46. M. Barilla and M. Spann, "Colour-based texture image classification using the complex wavelet transform", in 5th International Conference on Electrical Engineering, Computing Science and Automatic Control (2008), pp. 358-363.
47. A. Hanbury, U. Kandaswamy, and D. Adjeroh, "Illumination-invariant morphological texture classification", in Mathematical Morphology:40 Years On, C. Ronse, L. Najman, and E. Decencire, eds., Vol. 30 of Computational Imaging and Vision (Springer, 2005), pp. 377-386.
48. A. Oliva and A. Torralba, "Modeling the shape of the scene: a holistic representation of the spatial envelope", Int. J. Comput. Vis. 42, 145-175 (2001).
49. O. L. Junior, D. Delgado, V. Gonçalves, and U. Nunes, "Trainable classifier-fusion schemes: an application to pedestrian detection", in Intelligent Transportation Systems (2009).
50. C.-H. Chan, J. Kittler, and K. Messer, "Multispectral local binary pattern histogram for component-based color face verification", in 1st IEEE International Conference on Biometrics: Theory, Applications, and Systems (2007), pp. 1-7.
51. H. Jégou, M. Douze, C. Schmid, and P. Pérez, "Aggregating local descriptors into a compact image representation", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2010), pp. 3304-3311.
52. A. Vedaldi and K. Lenc, "MatConvNet-convolutional neural networks for MATLAB", arXiv:1412.4564 (2014).
53. A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks", in Advances in Neural Information Processing Systems (2012), pp. 1097-1105.
54. K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman, "Return of the devil in the details: delving deep into convolutional nets", arXiv:1405.3531 (2014).
55. M. D. Zeiler and R. Fergus, "Visualizing and understanding convolutional networks", in Computer Vision-ECCV 2014 (Springer, 2014), Vol. 8689, pp. 818-833.
56. P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun, "Overfeat: Integrated recognition, localization and detection using convolutional networks", arXiv:1312.6229 (2013).
57. K. Simonyan and A. Zisserman, "Very deep convolutional networks for large-scale image recognition", arXiv:1409.1556 (2014).
58. B. Funt, F. Ciurea, and J. Mccann, "Retinex in MATLAB", J. Electron. Imaging 13, 112-121 (2000).
59. J. McCann, "Lessons learned from Mondrians applied to real images and color gamuts", in Color and Imaging Conference (1999), pp. 1-8.
60. J. Frankle and J. McCann, "Method and apparatus for lightness imaging", U. S. patent 4384336 (May 17, 1983).
61. G. Finlayson and E. Trezzi, "Shades of gray and colour constancy", in Color and Imaging Conference (2004), pp. 37-41.
62. J. Van De Weijer, T. Gevers, and A. Gijsenij, "Edge-based color constancy", IEEE Trans. Image Process. 16, 2207-2214 (2007).
63. A. Gijsenij, T. Gevers, and J. Van De Weijer, "Improving color constancy by photometric edge weighting", IEEE Trans. Pattern Anal. Mach. Intell. 34, 918-929 (2012).