@inproceedings{9ae6cd3614894ef0b74a9ac7a18d84c1,
title = "Extracting Fourier descriptors from compressive measurements",
abstract = "Fourier descriptors (FDs) are shape-based features for the recognition of two-dimensional connected shapes. We propose a method that can extract FDs of an object directly from compressive measurements without reconstructing the image. Our method entails estimating the edges via discrete horizontal and vertical image gradients from compressive measurements. Fourier descriptors are then extracted from the thresholded edges. One of the main advantages of the proposed method is that it requires fewer number of compressive measurements to estimate FDs than required to estimate the original image. Various numerical experiments on synthetic and real data demonstrate the effectiveness of the proposed method.",
keywords = "compressed sensing, compressive sampling, feature extraction, Fourier descriptors",
author = "Puyang Wang and Patel, {Vishal M.}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 ; Conference date: 05-03-2017 Through 09-03-2017",
year = "2017",
month = jun,
day = "16",
doi = "10.1109/ICASSP.2017.7953059",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4755--4759",
booktitle = "2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings",
}