Thresholding is a method of image segmentation used in image processing to discern the boundaries of an object from its background. Semi-transparent particles, such as protein aggregates, are often mischaracterized or even undetected by most imaging particle analyzers when thresholding is missing or improperly configured.
Dark pixel thresholding, offered by most imaging particle analyzers, fails to discern particulate matter when it is lighter than the imaged background. Utilization of both dark and light pixel thresholding enables the detection of particulates expressing ranges in opacity (opaque to transparent) and improves the particle analyzer’s ability to detect, image, and analyze semi-transparent particles.
In our new white paper, we review the principles of dark and light pixel thresholding, and how these functions, along with VisualSpreadsheet’s neighborhood analysis, are necessary to accurately analyze semi-transparent particles. By understanding the issues of semi-transparent particle analysis and making it easy to optimize the system to account for them, FlowCam provides accurate particle characterization, count, and concentration.