12Binary Particle Classification

By using classification functions, objects with various shapes can be recognized, characterized, and sorted. Binary particle classification identifies an unknown object in a binary image by comparing a set of its significant features with a set of features that conceptually represent classes of known samples. For this purpose, the software needs to be trained using individual object images with significant unique features to create classes. The classes will be compared with unknown image samples during the classification process. The Binary Particle Classification method is different from geometric matching and pattern matching in that it is based on particle analysis of binary images. While Binary Particle Classification is discussed here, keep in mind that geometric matching is based on extraction of information on the boundary curve of objects and pattern matching is based on pixel intensity of image. The merits and demerits for each of the image analysis methods should be considered before selecting the best algorithm for sorting or inspecting of objects.

Binary particle classification is a fast method when the objects need to be sorted. However, this method will not find occluded objects because the method is based on binary images and two or more occluded objects are considered as one object of a different shape. Note that any acquired grayscale image of the objects will need to have good contrast with respect to background and that the ...

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