Related Concept Videos
Topographic Surveying and Contours
Light Acquisition
Basic Plant Anatomy: Roots, Stems, and Leaves
Anatomy of Chloroplasts
The Anatomy of Chloroplasts
Structure of...
Methods of Obtaining Topography
You might also read
Related Articles
Articles linked to this work by shared authors, journal, and citation graph.
Role of humoral immunity against hepatitis B virus core antigen in the pathogenesis of acute liver failure.
Infection with hepatitis C virus depends on TACSTD2, a regulator of claudin-1 and occludin highly downregulated in hepatocellular carcinoma.
Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.
Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.
Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.
Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.
Deep learning based two-way feature depiction model for brain tumor detection.
Related Experiment Video
Updated: Feb 17, 2026

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement
Published on: January 21, 2013
Contour recognition of complex leaf shapes.
1Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.
This study introduces a novel image analysis method to accurately capture leaf shape, even with overlapping lobes. This automated technique simplifies botanical taxonomy and herbarium specimen analysis.
Area of Science:
- Botany
- Image Analysis
- Computational Biology
Background:
- Leaf shape is a crucial taxonomic characteristic.
- Automated leaf contouring is hindered by overlapping lobes, necessitating manual tracing.
- Manual tracing is time-consuming and can introduce inaccuracies.
Purpose of the Study:
- To develop an automated method for accurately determining leaf shape, even with overlapping lobes.
- To overcome the limitations of manual contouring in botanical image analysis.
- To provide a more efficient and accurate approach for leaf shape characterization.
Main Methods:
- Acquisition of leaf images using a transilluminator.
- Two-level image segmentation to represent all leaf components in a single binary image.
- Contouring and concatenation of binary outlines to form a single, accurate leaf contour.
Main Results:
- Successfully achieved accurate leaf contouring despite the presence of touching or overlapping lobes.
- The method represents all leaf components, including overlapping lobes and closed sinuses, in a unified binary image.
- The generated contour accurately reproduces the complex leaf shape.
Conclusions:
- The described method effectively automates leaf shape acquisition, overcoming challenges posed by overlapping lobes.
- This technique offers a significant advancement for botanical taxonomy and the analysis of fragile herbarium specimens.
- The automated approach enhances efficiency and accuracy in leaf shape analysis for diverse plant species.

