Skip links to main content
Logo of Geometric Image Processing Laboratory,
Computer Science Department Home
Technion Home Page

Projects Last Projects

Corn Plant Segmentation

Snir Homsky and Iliya Rubinchik

Supervised by Alon Zvirin and Yaron Honen


Mask R-CNN is a conceptually simple, flexible, and general framework for object instance segmentation which efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance. This Project tackles the task of corn plant segmentation given a partially annotated small dataset using Mask R-CNN. We present a workflow for producing a large dataset from a small given dataset, which includes image augmentation, generation of artificial plant images, and generation of artificial images simulating real greenhouse scenes. Finally, we present results on leaf segmentation as well as whole plant segmentation, and discuss these results.

Project Corn Plant Segmentation Picture 1
Project Report

Please, see project report.

Final Presentation

Please, see final presentation.

Copyright © 2016 by Geometric Image Processing Lab. All rights reserved.