The client is the one of the most successful Australian biotechnology company.
The challenge was to create a solution that would allow the analysis of microscopic photos of microorganisms to count them, categorize and describe subspecies.
The processing pipeline consists of two stages based on artificial neural networks. It detects microorganisms and then segments their bodies to determine their surface on the image. To achieve such a precise segmentation, it's necessary to overexpose the image on a molecular level with support from other fields such as physics, mathematics, technology and more.
Flyps achieved a 95% recognition level accuracy and increased the high-resolution photo analyse time from 30 sec to 2 sec. Problems we had to overcome with our solutions:
This case study shows our project related to image processing and computer vision. The main goal was to achieve significant performance acceleration of existing solution.