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Published in:
Comparison of Statistical Features for Medical Colour Image Classification Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Improving FREAK Descriptor for Image Classification

Authors : Cristina Hilario Gomez, Kartheek Medathati, Pierre Kornprobst, Vittorio Murino, Diego Sona

Published in: Computer Vision Systems

Publisher: Springer International Publishing

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Abstract

In this paper we propose a new set of bio-inspired descriptors for image classification based on low-level processing performed by the retina. Taking as a starting point a descriptor called FREAK (Fast Retina Keypoint), we further extend it mimicking the center-surround organization of ganglion receptive fields. To test our approach we compared the performance of the original FREAK and our proposal on the 15 scene categories database. The results show that our approach outperforms the original FREAK for the scene classification task.

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Literature
1.
Alahi, A., Ortiz, R., Vandergheynst, P.: FREAK: fast retina keypoint. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 510–517 (2012)
2.
Bradski, G.: The opencv library. Dr. Dobb’s J. Softw. Tools 25, 120–126 (2000)
3.
Chichilnisky, E.J.: A simple white noise analysis of neuronal light responses. Netw.: Comput. Neural Syst. 12(2), 199–213 (2001)MATHCrossRef
4.
Lazebnik, S., Schmid, C., Ponce, J.: Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2169–2178. IEEE Computer Society (2006)
5.
Leutenegger, S., Chli, M., Siegwart, R.: Brisk: binary robust invariant scalable keypoints. In: ICCV 2011, pp. 2548–2555 (2011)
6.
Meng, X., Wang, Z., Wu, L.: Building global image features for scene recognition. Pattern Recogn. 45(1), 373–380 (2012)CrossRef
7.
Oliva, A., Torralba, A.: Modeling the shape of the scene: a holistic representation of the spatial envelope. Int. J. Comput. Vision 42(3), 145–175 (2001)MATHCrossRef
8.
Oliva, A., Torralba, A.: Building the gist of a scene: the role of global image features in recognition. Prog. Brain Res. 155, 23–36 (2006)
9.
Quattoni, A., Torralba, A.: Recognizing indoor scenes. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 413–420 (2009)
10.
Tola, E., Lepetit, V., Fua, P.: DAISY: an efficient dense descriptor applied to wide baseline stereo. IEEE Trans. Pattern Anal. Mach. Intell. 32(5), 815–830 (2010)CrossRef
11.
Tuytelaars, T.: Dense interest points. In: The Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2010, pp. 2281–2288, San Francisco, CA, USA, 13–18 June 2010 (2010)
12.
13.
Vu, N.-S., Nguyen, T.P., Garcia, C.: Improving texture categorization with biologically inspired filtering. Image Vis. Comput. 32, 424–436 (2013)CrossRef
14.
Wang, J., Wang, X., Yang, X., Zhao, A.: CS-FREAK: an improved binary descriptor. In: Tan, T., Ruan, Q., Wang, S., Ma, H., Huang, K. (eds.) IGTA 2014. CCIS, vol. 437, pp. 129–136. Springer, Heidelberg (2014)
15.
Whiten, C., Laganiere, R., Bilodeau, G.A.: Efficient action recognition with MoFREAK. In: Proceedings of the 2013 International Conference on Computer and Robot Vision, pp. 319–325. IEEE Computer Society (2013)
16.
Wohrer, A.: Model and large-scale simulator of a biological retina with contrast gain control. Ph.D. thesis, University of Nice Sophia-Antipolis (2008)
17.
Wu, J., Rehg, J.M.: Centrist: a visual descriptor for scene categorization. IEEE Trans. Pattern Anal. Mach. Intell. 33(8), 1489–1501 (2011)CrossRef
Metadata
Title
Improving FREAK Descriptor for Image Classification
Authors
Cristina Hilario Gomez
Kartheek Medathati
Pierre Kornprobst
Vittorio Murino
Diego Sona
Copyright Year
2015
Book
Computer Vision Systems

Print ISBN: 978-3-319-20903-6

Electronic ISBN: 978-3-319-20904-3

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-20904-3_2

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