Design of a 3D-printed microscope for imaging with an event-camera

Optical cameras have been very successfully used for 3D vision and robotic navigation in texture rich environments and good visibility conditions. However, they have strong limitations in more complex scenarios where the environment is either very dynamic or subject to poor illumination conditions. In this project, you will explore a new imaging modality, referred to as neuromorphic (or event-based) imaging and investigate how it can help solve these problems [1]. Event-cameras offer very high frame rates and can be used in with fast moving objects (more than 10k frames per second) [2] and in this project, the student will adapt and build a microscope embedding such a camera. The prototype will then be tested for medical applications.

The project will be divided into 2 main topics including
- Design and realisation of a motorised 3D printed microscope
- Implementation of processing pipeline allowing object detection and classification

This project is multidisciplinary, at the interface between robotics and signal/image processing. This project will mainly use python/matlab. The microscope will be controlled via an Arduino or a Raspberry Pi and will be based on existing 3D-printed microscope designs such as those developed within The Openflexture project [3].

References
[1] http://rpg.ifi.uzh.ch/research_dvs.html
[2] Prophesee (camera manufacturer): https://www.prophesee.ai
[2] The OpenFlexture Project: https://openflexure.org/projects/microscope/

Supervisor name: 
Yoann Altmann
Supervisor and Deputy email addresses: 
Y.Altmann@hw.ac.uk