This Repository is aimed at reading handwritten images of numbers and identifying the number written in it using Image Segmentation and Convolutional Neural Networks
The image segmentation algorithm uses contour tracing algorithm to separate the characters from a handwritten number. For Example :- 1567 should be separated as 1, 5, 6 and 7.
The digit recognition part is done by using a trained Convolutional Neural Network. Details about training and dataset can be found in my repository https://github.com/SparshaSaha/Neural-Nets/blob/master/Coursera%20Handwritten%20digits%20Recognition/Coursera_digit_recog_using_CNN.ipynb . This trained network is used to predict each digit and then ultimately predict the number.
Segmentation_utilities.py is the utility API for Image Segmentation
Python3
TensorFlow
TFlearn
PIL
Scipy
Numpy
Matplotlib
Jupyter-Notebook
The project can be run by using the CNN Classifier.ipnb file and providing the name of the image file which contains the image of the number to be classified.