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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(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 2MB |
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 |
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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) |
Laboratory name: | |
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Deposited On: | 31 Mar 2020 08:52 |
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