FRI Modelling of Fourier Descriptors

Kamath, AJ and Rudresh, S and Seelamantula, CS (2019) FRI Modelling of Fourier Descriptors. In: 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019, 12 - 17 May 2019, Brighton, pp. 5092-5096.

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Abstract

Fourier descriptors are used to parametrically represent closed contours. In practice, a finite set of Fourier descriptors can model a large class of smooth contours. In this paper, we propose a method for estimating the Fourier descriptors of a given contour from its partial samples. We take a sampling-theoretic approach to model the x and y coordinate functions of the shape and express them as a sum of weighted complex exponentials, which belong to the class of finite-rate-of-innovation (FRI) signals. The weights represent the Fourier descriptors of the shape. We use the FRI framework to estimate the shape parameters reliably from noisy and partial measurements. We model non-uniformities in sampling using the sampling jitter model and employ a prefiltering process to reduce the effect of measurement noise and jitter. The average sampling interval is estimated by a block annihilating filter, which is then followed by the estimation of Fourier descriptors using least-squares fitting. We demonstrate the robustness of the proposed algorithm to noise and sampling jitter. Monte Carlo performance analysis shows that the variances of the estimators are close to the Cramér-Rao lower bounds. We present results for outlining shapes in synthetic as well as real images. © 2019 IEEE.

Item Type:	Conference Paper
Publication:	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords:	Acoustic noise; Fourier transforms; Jitter; Speech communication, block annihilation; Coordinate functions; Effect of measurements; Finite rate of innovations; Finite rate of innovations (FRI); Fourier descriptors; Least squares fitting; Parametric curve, Audio signal processing
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	27 Jan 2023 09:21
Last Modified:	27 Jan 2023 09:21
URI:	https://eprints.iisc.ac.in/id/eprint/78389

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