Image invariant description based on local Fourier-Mellin transform

Abstract : In this paper, we present a novel approach for real-time object identification on a mobile platform. First, our system detects keypoints within a scaled pyramid-based FAST detector and then descriptors of the object of interest are computed using an Analytical Fourier-Mellin transform. The Fourier-Mellin is used in similarity studies due to its invariance property and discrimination power. In this approach, we exploited information from the phase of Fourier Transform instead of magnitude applied on patches. The phase carries more information and handle, particularly, rotation and light changes. Finally, experiments are conducted to evaluate the system performances in terms of accuracy, robustness and computational efficiency as well
Type de document :
Communication dans un congrès
ICSIPA 2017 : IEEE International Conference on Signal and Image Processing Applications, Sep 2017, Kuching, Malaysia. IEEE Computer Society, Proceedings ICSIPA 2017 : IEEE International Conference on Signal and Image Processing Applications, pp.159 - 163, 2017, 〈10.1109/ICSIPA.2017.8120598〉
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01691604
Contributeur : Médiathèque Télécom Sudparis & Institut Mines-Télécom Business School <>
Soumis le : mercredi 24 janvier 2018 - 10:41:26
Dernière modification le : jeudi 31 mai 2018 - 09:12:02

Identifiants

Citation

Yassine Lehiani, Madjid Maidi, Marius Preda, Faouzi Ghorbel. Image invariant description based on local Fourier-Mellin transform. ICSIPA 2017 : IEEE International Conference on Signal and Image Processing Applications, Sep 2017, Kuching, Malaysia. IEEE Computer Society, Proceedings ICSIPA 2017 : IEEE International Conference on Signal and Image Processing Applications, pp.159 - 163, 2017, 〈10.1109/ICSIPA.2017.8120598〉. 〈hal-01691604〉

Partager

Métriques

Consultations de la notice

38