Image analysis for particle size recognition of bioprocesses in liquid environment

Abstract

© 2016 Mayar Aly Atteya et al. Background: Actually, particle size recognition plays an important issue in many applications those applied on microscopic imaging. Today, many developments yield to replace the oil fish ingredients by microalgae products. Indeed, the microalgae cells lives in liquid environment, the size parameter can differentiate between the biological cells, grain stones and air bubbles. Materials and Methods: This study presents a method for improving the automation of particle recognition and counting using a recently developed SOPAT-probe (smart on-line particle analysis technology), a photo optical image acquisition device. This method includes image de-noising, image binarization, image enhancement and watershed segmentation. Results: This method approves that the microalgae particles can be identified correctly with accuracy reaches up to 99%. Conclusion: The proposed method was used to develop an advanced method for a vision-based system that expected to automatically detect, classify and track the active cells using the recently developed SOPAT-system. The result is showed statistically and graphically by computing the area histogram.