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Springer, Lecture Notes in Computer Science, p. 14-23, 2015

DOI: 10.1007/978-3-319-20904-3_2

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Improving FREAK Descriptor for Image Classification

Proceedings article published in 2015 by Cristina Hilario Gomez, N. V. Kartheek Medathati, Pierre Kornprobst, Vittorio Murino, Diego Sona ORCID
This paper is available in a repository.
This paper is available in a repository.

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Abstract

In this paper we propose a new set of bio-inspired descrip- tors 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 com- pared the performance of the original FREAK and our proposal on the 15 scene categories database. The results show that our approach out- performs the original FREAK for the scene classification task.