Image invariant description based on local Fourier-Mellin transform

Yassine Lehiani, Madjid Maidi, Marius Preda, Faouzi Ghorbel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages159-163
Number of pages5
ISBN (Electronic)9781509055593
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes
Event5th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017 - Kuching, Sarawak, Malaysia
Duration: 12 Sept 201714 Sept 2017

Publication series

NameProceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017

Conference

Conference5th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017
Country/TerritoryMalaysia
CityKuching, Sarawak
Period12/09/1714/09/17

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