3. Handwriting recognition is a Python based project.
It will recognize the handwritten texts which is not
understandable manually.
It will represent the handwritten texts into Digital format.
It will enable the user to read complicated text.
4. In today’s world, we often encounter the situation in which we
feel difficult to understand and read the complex handwritten
texts.
Due to this problem, content may lose it’s originality and
credibility.
These reasons motivates us to create the handwriting
recognition project.
5. This project is written in Python language as it is simple and
easy to use.
This project makes use of image recognition and machine
learning technology.
This project also makes use of Mnist dataset.
6. Mnist dataset is present in form of grid. This grid is
combination of pixel which are colored in black and white.
Program recognizes the text on the basis of variation of color
between black and white of these pixels.
7.
8. Program will take some data from Mnist library as input
for training itself which comes under machine learning.
After training itself program will recognize the next input
letter or digit.
Output will be clear recognized image of blur text that could
be easily understood.
9. This project may not be 100 percent accurate as the machine
need to be trained on predefined dataset in order to predict
the correct output. However it may not understand the each
letter or digit of handwritten text correctly.
This may result in incorrect output and reduce a little
accuracy of code.
10. This project will help me in enhancing my knowledge in
various topics like python, image recognition, machine
learning, etc.
If this project is successful, it will be useful to recognize
blurry or irregular handwritten text. It will increase the
efficiency of analyzing the text which is difficult to read
manually.
11. To develop this project I took reference from Github,
YouTube, learned some concepts of python from geeks of geeks,
etc.
