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Automatic detection of individual and touching moths from trap images by combining contour-based and region-based segmentation

Bakkay, Mohamed Chafik and Chambon, Sylvie and Rashwan, Hatem A. and Lubat, Christian and Barsotti, Sébastien Automatic detection of individual and touching moths from trap images by combining contour-based and region-based segmentation. (2018) IET Computer Vision, 12 (2). 138-145. ISSN 1751-9632

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Official URL: https://doi.org/10.1049/iet-cvi.2017.0086

Abstract

Insect detection is one of the most challenging problems of biometric image processing. This study focuses on developing a method to detect both individual insects and touching insects from trap images in extreme conditions. This method is able to combine recent approaches on contour-based and region-based segmentation. More precisely, the two contributions are: an adaptive k -means clustering approach by using the contour's convex hull and a new region merging algorithm. Quantitative evaluations show that the proposed method can detect insects with higher accuracy than that of the most used approaches.

Item Type:Article
HAL Id:hal-02538367
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Other partners > SiConsult (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited On:31 Mar 2020 08:52

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