An effective and friendly tool for seed image analysis

• Published in: arXiv.org
• Main Authors: Loddo, Andrea, Cecilia Di Ruberto, A M P G Vale, Ucchesu, Mariano, Soares, J M, Bacchetta, Gianluigi
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 23.07.2021
• Subjects: Botany; Computer Science - Computer Vision and Pattern Recognition; Feature extraction; Image analysis; Image classification; Seeds
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2103.17213

Image analysis is an essential field for several topics in the life sciences, such as biology or botany. In particular, the analysis of seeds (e.g. fossil research) can provide significant information on their evolution, the history of agriculture, plant domestication and knowledge of diets in ancient times. This work aims to present software that performs image analysis for feature extraction and classification from images containing seeds through a novel and unique framework. In detail, we propose two plugins \emph{ImageJ}, one able to extract morphological, textual and colour features from seed images, and another to classify seeds into categories using the extracted features. The experimental results demonstrated the correctness and validity of both the extracted features and the classification predictions. The proposed tool is easily extendable to other fields of image analysis.