TITLE:
Facilitating the Automatic Characterisation, Classification and Description of Biological Images with the VisionBioShape Package for R
AUTHORS:
Biel Stela, Antonio Monleón-Getino
KEYWORDS:
Computer Vision, Biological Images, Ecology, Statistics, Elliptic Fourier Descriptor, Principal Component Analysis
JOURNAL NAME:
Open Access Library Journal,
Vol.3 No.10,
October
26,
2016
ABSTRACT: Here, we present the VisioBioshapeR package for R [R Core, 2014]. This new library is a comprehensive, multifunctional toolbox designed to automatically analyse biological images. The package extends other common libraries (Momocs, ShapeR) used for biological shape analysis by allowing the user to extract closed contour outlines automatically from reading binary images. Current functionalities of VisioBioshapeR include: random extraction of image coordinates, analysis of the shape of a biological image by the elliptic Fourier descriptor (EFD) method, extraction of an image characteristic vector using multivariate principal component analysis (PCA) and geometrical analysis. The image vector of characteristics can be directly exported to a wide range of statistical packages in R and can be used to perform classification or other types of analysis in order to sort new images into classes. The package could prove useful in studies of any two-dimensional images and is presented with three examples of its application in ecology. The library is useful when multiple images are processed at a time and we wish to automate their analysis for example for recognition of images from patterns.