Isolating Objects via Particle Filtering
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Description
Particle filtering uses the results of particle analysis to remove or retain particles with specified characteristics. It is useful for extracting objects from an image based on their distinguishing features. The key to the success of particle filtering is determining the parameters which best distinguish the objects of interest from objects which are to be removed from the image.
Common Applications
A prerequisite for particle filtering is that the particles be identified and analyzed. The contrast and sharpness of the original image determine whether or not the identification will be possible with simple thresholding techniques. Common applications include checking for defects in manufactured components and analysis of biological tissues (cell counting, tumor detection, organ identification, and so on).
What To Expect
The results obtained by particle filtering vary depending on the uniqueness of the objects involved. In many cases, a single particle filter operation will identify the object of interest correctly and eliminate other particles. In more complicated images, knowledge of the basic structure of the image may be required to make a final decision between several similar objects. For example, you may know that there are several similar objects, but the one you are looking for is the leftmost one in the image.
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