AN UNCONSTRAINED ELLIPSE FITTING TECHNIQUE AND APPLICATION TO OPTIC CUP SEGMENTATION

Sridhar, Harsha and Kumar, Harish JR and Jois, Subramanya and Seelamantula, Chandra Sekhar (2018) AN UNCONSTRAINED ELLIPSE FITTING TECHNIQUE AND APPLICATION TO OPTIC CUP SEGMENTATION. In: Global Conference on Signal and Information Processing (GlobalSIP), NOV 26-29, 2018, Anaheim, CA, USA, pp. 514-518.

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Abstract

We present a novel method for fitting an ellipse to scattered data based on least-squares minimization. The new technique has several advantages over the standard ellipse fitting techniques. For one, it is constraint-free and computationally inexpensive thus making it easy to implement. Also, despite the absence of constraints, execution of the model always results in an ellipse fit. Additionally, the model results in a singular solution for a given set of datapoints. The proposed model is compared with standard techniques and shown to have the ability to fit an accurate ellipse even when other methods either fail to be ellipse-specific or take up excessive computation time for execution. An application to the problem of segmentation of the optic cup in retinal fundus images, is also presented. Experimental validation and performance comparisons show that the proposed technique is competitive with the state-of-the-art methods.

Item Type:	Conference Paper
Publication:	2018 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2018)
Series.:	IEEE Global Conference on Signal and Information Processing
Publisher:	IEEE
Additional Information:	Copyright for this article belongs to IEEE
Keywords:	Ellipse fit; least-squares minimization; optic cup; segmentation; constraint-free optimization
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	29 May 2019 10:48
Last Modified:	30 May 2019 17:25
URI:	http://eprints.iisc.ac.in/id/eprint/62350

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