Handwriting recognition is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices.
But also we can define it as shape analysis or shape recognition by using image processing applications.
*Including boxes
*Moment descriptors
*Guzman polygons
*Freeman chain coding
*Fourier descriptors
- invariance with translation
- invariance with rotation
- invariance with scaling
-Low frequency components contain information about the general features of the shape, and the higher frequency components contain finer details of the shape.
-Though different people may have different drawing habits, the subset of the low frequency coefficient tend to be similar for the same electronic component.
-So although the number of coefficients generated from the Fourier transform is usually large, the dimensions of the Fourier descriptors used for shape recognition can be greatly reduced.
