For each character, resize its image to 20x15 pixels and then extract its fea. Extract each character in the input image independently.ġ.  Network has epchos of 7000 and a goal of 0.Īfter training the data the network and saving it, it will be ready for working.ġ.

The target matrix created is a 36x36 matrix. The features of the first dataset image is placed in a 15x36 feature array withĮach feature resides a row in this array. This process is done for all the dataset elements. The sum of the elements of this column is 12. The sum in the first element in that column.įor example, in the following figure you can simply note that the first column Featuresįrom every 20x15 image, find the sum of all elements in the column k and place

So many features can be used when trying to recognize characters. Same size to make the features extracted comparable.Īfter analyzing the images` sizes, the size that can match all the images is I have choose to use the Arial font with size 20 points while being Bold to cre-Īte the dataset of numbers and English letters.Īfter capturing the image for each character, next is to make all images has the Pattern recognition project when being undergraduate student at 2013.įirst of all, when trying to use neural network, so you for sure want to know the Recognize characters using feed forward back propagation neural network as a This file contains a simple description about what I have created about how to Recognition (OCR) System Using Artificial Neural Net-įaculty of Computers and Information (FCI) Very Simple Automatic English Optical Character MATLAB Code + Description : Very Simple Automatic English Optical Character Recognition (OCR) System using Artificial Neural Networks (ANNs) The MATLAB code of the system is also available in the document. This file contains a simple description about what I have created about how to recognize characters using feed forward back propagation neural network as a pattern recognition project when being undergraduate student at 2013.

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