Particle Image Understanding–A Primer

by Lew Brown, Director of Marketing, Fluid Imaging Technologies, Inc.

Abstract
This paper will discuss the use of pattern recognition techniques to identify and differentiate different particle types contained in a heterogeneous solution. This application involves imaging the microscopic particles in real time as they flow in a solution, segregating each individual particle as a separate image, and then applying pattern recognition techniques to differentiate the individual particle types. A framework for discussing the complexity of a pattern recognition operation in this application will be proposed, along with some specific examples showing how this framework applies.

Introduction
The computational method known as “pattern recognition” has been around for many years now, beginning early in the 1960s with military uses centered upon “remote sensing” (aerial and satellite imaging). Use of these techniques then expanded into the field of medical imaging, machine vision and others. The enormous computational demands of these applications limited early use of the technologies to institutions and organizations that could afford the high cost of the hardware necessary to perform these operations.

The reason for the high cost of use of the technology has been that “pattern recognition” attempts to mathematically duplicate cognitive processes performed by the human eye/brain combination with ease. Indeed, many simple “pattern recognition” operations that we as humans take for granted in our day to day lives are extremely difficult (if not impossible) to reproduce using computational methods. As the cost of computing hardware has dropped precipitously while the performance of this hardware has risen exponentially, it has become increasingly possible for some of the most basic pattern recognition operations to be performed on common, inexpensive computing platforms such as Personal Computers.

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