# An effective and friendly tool for seed image analysis

arXiv: https://arxiv.org/abs/2103.17213 · HTML: https://mlsanity.com/paper/2103.17213/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 58 references that are in the map.
- First posted on arXiv 31 Mar 2021.

## Builds on (most cited first, 3 of 3)

- [Using Deep Learning for Image-Based Plant Disease Detection](https://mlsanity.com/paper/1604.03169/) (2016)
- [Deep learning in agriculture: A survey](https://mlsanity.com/paper/1807.11809/) (2018)
- [A new automatic approach to seed image analysis: From acquisition to segmentation](https://mlsanity.com/paper/2012.06414/) (2020)

## Abstract (arXiv)

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 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.