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Support Vector Machine (SVM) Recognition Approach adapted to Individual and Touching Moths Counting in Trap Images

Bakkay, Mohamed Chafik and Chambon, Sylvie and Rashwan, Hatem A. and Lubat, Christian and Barsotti, Sébastien Support Vector Machine (SVM) Recognition Approach adapted to Individual and Touching Moths Counting in Trap Images. (2018) In: Workshop on Visual observation and analysis of Vertebrate And Insect Behavior @ 24th International Conference on Pattern Recognition (VAIB @ IPCR2018), 20 August 2018 (Beijing, China).

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Official URL: http://homepages.inf.ed.ac.uk/rbf/VAIB18PAPERS/vaib18bakkay.pdf

Abstract

This paper aims at developing an automatic algorithm for moth recognition from trap images in real-world conditions. This method uses our previous work for detection [1] and introduces an adapted classification step. More precisely, SVM classifier is trained with a multi-scale descriptor, Histogram Of Curviness Saliency (HCS). This descriptor is robust to illumination changes and is able to detect and to describe the external and the internal contours of the target insect in multi-scale. The proposed classification method can be trained with a small set of images. Quantitative evaluations show that the proposed method is able to classify insects with higher accuracy (rate of 95.8%) than the state-of-the art approaches.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-02498757
Audience (conference):International conference proceedings
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:
Funders:
BPIFrance : Banque Publique d'Investissement (France) - Région Occitanie (France) - FEDER : Fonds européen de développement régional (Europe)
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Deposited On:25 Feb 2020 12:08

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