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Article Dans Une Revue IET Computer Vision Année : 2018

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

Résumé

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.
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Dates et versions

hal-02538367 , version 1 (09-04-2020)

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Mohamed Chafik Bakkay, Sylvie Chambon, Hatem A. Rashwan, Christian Lubat, Sébastien Barsotti. Automatic detection of individual and touching moths from trap images by combining contour-based and region-based segmentation. IET Computer Vision, 2018, 12 (2), pp.138-145. ⟨10.1049/iet-cvi.2017.0086⟩. ⟨hal-02538367⟩
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