Embryo Detection System Development

Developing a proof of concept (POC) mechanism and prototype system to detect embryo presence in eggs during the initial post-laying period, with primary emphasis on optimizing both speed and accuracy metrics.

The methodological approach established a comprehensive solution strategy centered on controlling the interdisciplinary interfaces critical to project success. After identifying fundamental challenges across biophysics, photography, image processing, and machine learning domains, I meticulously mapped how each discipline would contribute to the integrated solution architecture.

Using lighting engineering, optical systems, photographic technology, image processing algorithms, and machine learning frameworks, I orchestrated a cohesive development process ensuring disciplinary alignment toward our unified objectives.

This systematically integrated approach culminated in a high-performance prototype that achieved 100% detection accuracy while delivering unprecedented processing speed and precision, fully satisfying all project requirements and establishing a robust foundation for further development.

Fertile VS Undeveloped Egg:

Initial Photography experiments:

Image preprocessing and classification:

Image preprocessing algorithm:

Highlighting of blood vessels algorithm:

POC Prototype (Egg fixture and optics):

POC Prototype