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Image Recognition Methods


Breaking out Features

Local Binary Patterns (LBP):

OCR Optical Character Recognition

Image correlation: Optical Mice

Browser Based Image Processing: Subtraction, Area Sum

Methods for detecting Optical Flow +

Synthetic Data: To collect large sample sets for character recognition, you can synthesize "fake" data (Artificial Data) by randomly pasting letters from a randomly selected font onto a randomly selected background with (perhaps) random distortions and rotations. The major advantage of doing this is that you don't have to "label" the data (know what character(s) are represented) because you made it from the label in the first place. It can also help in trouble shooting complex systems, by replacing a stage in a complex system with a "perfect" stage to see how much that effects the end product. E.g. if you are wondering how much background removal helps your OCR application, generate input images with no background.


See also:

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