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Building an adaptive UV imaging system for protein crystal detection.
Protein crystals fluoresce under UV light due to tryptophan and tyrosine present in their structure. In this project we aim to build an adaptive imaging system that can capture the fluorescence in protein crystals for detection in images.
Automated detection of protein crystals is a crucial and a challenging step in automated protein crystal harvesting. It Is known that, most of the protein crystals fluoresce under UV light due to tryptophan and tyrosine present in their structure. In this project we aim to build an adaptive imaging system that can capture the aforementioned fluorescence in protein crystals.
Student should know: C, C++
Helpful skills: Basic knowledge on image formation, Embedded C, Matlab
Automated detection of protein crystals is a crucial and a challenging step in automated protein crystal harvesting. It Is known that, most of the protein crystals fluoresce under UV light due to tryptophan and tyrosine present in their structure. In this project we aim to build an adaptive imaging system that can capture the aforementioned fluorescence in protein crystals.
Student should know: C, C++ Helpful skills: Basic knowledge on image formation, Embedded C, Matlab
- Selection of a suitable camera,
- Implementation of a simple frame grabber for the selected camera,
- Selection of the suitable UV source,
- Design and implementation of the hardware system that will establish the correct timing between the camera and the UV source,
- Adaptive optimization of the camera parameters for improving the quality of the resulting image.
- Selection of a suitable camera, - Implementation of a simple frame grabber for the selected camera, - Selection of the suitable UV source, - Design and implementation of the hardware system that will establish the correct timing between the camera and the UV source, - Adaptive optimization of the camera parameters for improving the quality of the resulting image.