%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Nguyen, H. H.
%A Ho, B. H.
%A Lai, H. P.
%A Tran, H. T.
%A Banuls, Anne-Laure
%A Prudhomme, J.
%A Le, H. T.
%T A lightweight keypoint matching framework for insect wing morphometric landmark detection
%D 2022
%L fdi:010085328
%G ENG
%J Ecological Informatics
%@ 1574-9541
%K Landmark ; Morphometric ; Keypoint matching ; Open-source
%M ISI:000812362600008
%P 101694 [9 ]
%R 10.1016/j.ecoinf.2022.101694
%U https://www.documentation.ird.fr/hor/fdi:010085328
%> https://www.documentation.ird.fr/intranet/publi/2022-09/010085328.pdf
%V 70
%W Horizon (IRD)
%X Geometric morphometrics has become an important approach in insect morphology studies because it capitalizes on advanced quantitative methods to analyze shape. Shape could be digitized as a set of landmarks from specimen images. However, the existing tools mostly require manual landmark digitization, and previous works on automatic landmark detection methods do not focus on implementation for end-users. Motivated by that, we propose a novel approach for automatic landmark detection, based on visual features of landmarks and keypoint matching techniques. While still archiving comparable accuracy to that of the state-of-the-art method, our framework requires less initial annotated data to build prediction model and runs faster. It is lightweight also in terms of implementation, in which a four-step workflow is provided with user-friendly graphical interfaces to produce correct landmark coordinates both by model prediction and manual correction. The utility iMorph is freely available at https://github.com/ha-usth/InsectWingLandmark, currently supporting Windows, MacOS, and Linux.
%$ 052 ; 020 ; 122