Character recognition system
To solve the tasks of character recognition we have developed the optical characters recognition system on basis of neural networks. The developed system consists of subsystem of raster image preprocessing and actually of recognition subsystem. Subsystem of raster image preprocessing allows improving the quality of recognition. Algorithm of recognition uses multilayer neural network to recognize a symbol. The advantages of the developed system include rather high stability against image defects, high processing speed of input data and ability to learn.
We are currently working on the development of the improved algorithm of recognition system based on representation of each class of symbols as a set of some unique elements and as a relation between these elements. Thus each symbol is represented as a set of unique features, which are invariant with respect to the print. The features selected in the original symbol are being compared with the features of standard symbols and the belonging of a symbol to a certain class is determined.
As a result of our work we will develop a library, which will be able to recognize texts in different languages on the images of various type including newspaper ads and image titles in video file. This library will be integrated with the Real Time Video Stream Recognition System.