A survey on image-based insect classification. (May 2017) - Martineau, Maxime; Conte, Donatello; Raveaux, Romain; Arnault, Ingrid; Munier, Damien; Venturini, Gilles
Abstract: Entomology has had many applications in many biological domains (i.e insect counting as a biodiversity index). To meet a growing biological demand and to compensate a decreasing workforce amount, automated entomology has been around for decades. This challenge has been tackled by computer scientists as well as by biologists themselves. This survey investigates fourty-four studies on this topic and tries to give a global picture on what are the scientific locks and how the problem was addressed. Views are adopted on image capture, feature extraction, classification methods and the tested datasets. A general discussion is finally given on the questions that might still remain unsolved such as: the image capture conditions mandatory to good recognition performance, the definition of the problem and whether computer scientist should consider it as a problem in its own or just as an instance of a wider image recognition problem. Abstract : Graphical abstract: Abstract : Highlights: Fourty-four about image-based insect recognition are scrutinized. Each paper is qualified from three perspectives: image capture, feature extraction and classification. Datasets used in the literature are investigated. A discussion is given in which several questions about the problem are raised.