Hessian-polar context: A descriptor for microfilaria recognition

Faroq AL-Tam; António dos Anjos; Hamid Reza Shahbazkia

doi:10.1007/s00138-020-01154-6

Hessian-polar context: A descriptor for microfilaria recognition

Faroq AL-Tam^*, António dos Anjos, Hamid Reza Shahbazkia

^*Corresponding author for this work

Department of Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

This paper presents a new effective descriptor for microfilaria. Since microfilaria is a thin elastic object, the proposed descriptor handles it locally. At each medial point of the microfilaria, the local structure of the microfilaria votes for a given shape. Accumulating these votes in the polar domain yields a rich descriptor. Experimental results show the effectiveness of the proposed approach when compared to a set of different well-established methods.

Original language	English
Article number	25
Number of pages	10
Journal	Machine Vision and Applications
Volume	32
Issue number	1
DOIs	https://doi.org/10.1007/s00138-020-01154-6
Publication status	Published - 02 Jan 2021

Keywords

Computer vision
Hessian-polar context
Machine learning
Microfilaria
Parasitics

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10.1007/s00138-020-01154-6

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title = "Hessian-polar context: A descriptor for microfilaria recognition",

abstract = "This paper presents a new effective descriptor for microfilaria. Since microfilaria is a thin elastic object, the proposed descriptor handles it locally. At each medial point of the microfilaria, the local structure of the microfilaria votes for a given shape. Accumulating these votes in the polar domain yields a rich descriptor. Experimental results show the effectiveness of the proposed approach when compared to a set of different well-established methods.",

keywords = "Computer vision, Hessian-polar context, Machine learning, Microfilaria, Parasitics",

author = "Faroq AL-Tam and {dos Anjos}, Ant{\'o}nio and Shahbazkia, {Hamid Reza}",

note = "Funding Information: The authors are grateful to Thamar university and Infectiop{\^o}le Sud, Marseille-France, and the Bill & Melinda Gates foundation. Publisher Copyright: {\textcopyright} 2021, Springer-Verlag GmbH Germany, part of Springer Nature.",

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doi = "10.1007/s00138-020-01154-6",

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AU - AL-Tam, Faroq

AU - dos Anjos, António

AU - Shahbazkia, Hamid Reza

N1 - Funding Information: The authors are grateful to Thamar university and Infectiopôle Sud, Marseille-France, and the Bill & Melinda Gates foundation. Publisher Copyright: © 2021, Springer-Verlag GmbH Germany, part of Springer Nature.

PY - 2021/1/2

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N2 - This paper presents a new effective descriptor for microfilaria. Since microfilaria is a thin elastic object, the proposed descriptor handles it locally. At each medial point of the microfilaria, the local structure of the microfilaria votes for a given shape. Accumulating these votes in the polar domain yields a rich descriptor. Experimental results show the effectiveness of the proposed approach when compared to a set of different well-established methods.

AB - This paper presents a new effective descriptor for microfilaria. Since microfilaria is a thin elastic object, the proposed descriptor handles it locally. At each medial point of the microfilaria, the local structure of the microfilaria votes for a given shape. Accumulating these votes in the polar domain yields a rich descriptor. Experimental results show the effectiveness of the proposed approach when compared to a set of different well-established methods.

KW - Computer vision

KW - Hessian-polar context

KW - Machine learning

KW - Microfilaria

KW - Parasitics

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VL - 32

JO - Machine Vision and Applications

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IS - 1

M1 - 25

ER -

Hessian-polar context: A descriptor for microfilaria recognition

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