Benchmarking Smartphone- and Depth Camera-Based 3D Fruit Reconstruction Against an Established Phenotyping Platform
- Beschreibung
This project investigates low-cost 3D fruit reconstruction using smartphone photogrammetry and depth camera imaging. Different fruits will be measured with both methods, and the resulting 3D models will be used to extract traits such as size, shape, and volume. The final results will be benchmarked against an established phenotyping platform to assess the accuracy, strengths, and limitations of these low-cost approaches for fruit phenotyping.
- Beschreibung des interdisziplinären Teils des Projekts
- This project combines agricultural science, computer vision, imaging technology, and data analysis. Participants will learn about fruit phenotyping and quality traits, while also working with smartphone imaging, depth sensing, open-source 3D reconstruction tools. The project shows how agriculture and digital technologies can be combined to develop affordable and practical phenotyping solutions.
- Projektzeitraum
- Sommersemester 2026
- Bewerbungszeitraum
- 07. bis 20.04.2026
- Durchführung
- semesterbegleitend
- Details zu Projektzeitraum und Durchführung
The project will be carried out during the winter semester. Fruit image acquisition using a smartphone and a depth camera, as well as simple reference measurements, will take place at the Institute of Agricultural Engineering (440e). Data processing, 3D reconstruction, trait extraction, and comparison with the institute’s phenotyping platform will be conducted on the institute’s computers.
- Studienfach
- offen für alle Studienfächer
- Betreuende
- Khandoker Ahammad, Prof. Dr. Joachim Müller, Janvier Ntwali, Iris Ramaj
- Institut
- Institut für Agrartechnik (440) (Tropen und Subtropen gruppen)
- Sprache
- deutsch
- Teilnehmendenanzahl
- min. 1, max. 2
- Arbeitsaufwand
-
ca. 180 Stunden pro Teilnehmende:r
| 6
ECTS-Punkte
Arbeitsaufwand (Stunden und ggf. ECTS) sind ungefähre Angaben. Die tatsächlich vergebenen ECTS-Punkte ergeben sich aus der tatsächlich geleisteten Arbeit.
- Für dieses Projekt ist kein Motivationsschreiben des Studierenden erforderlich
- Projektart
- experimentell
- Lernziele
-
Die Teilnehmende lernen in diesem Projekt:
In this project, participants will learn to:
- formulate and address a scientific research question in fruit phenotyping
- understand the principles of smartphone photogrammetry and depth-based 3D reconstruction
- acquire and process fruit images using low-cost imaging devices
- generate and analyze 3D fruit models with open-source software
- Extract structural fruit traits from reconstructed models
- Compare low-cost reconstruction results with measurements from an established phenotyping platform
- Anmerkungen für Studierende
- Motivated and interested in the topic.
- It is possible to integrate the project into a Master thesis
- Schlagworte
- 3D fruit phenotyping, smartphone photogrammetry, depth camera, low-cost imaging, 3D reconstruction, phenotyping platform