The primary goal of this project is to presents an efficient Devanagari character classification model.
Devanagari character recognition is the ability of a computer to receive and interpret handwritten input from sources such as paper documents, photographs, touch-screens and other devices. Handwritten Devanagari Characters are more complex for recognition than corresponding English characters due to many possible variations in order, number, direction and shape of the constituent strokes. The main purpose of this project is to introduce a new method for recognition of handwritten Devanagari characters using Segmentation, Image Processing and Artificial Intelligence. The whole process of recognition includes two phases- segmentation of characters into line, word and characters and then recognition through feed-forward neural network.
Keywords: Deep learning, ANN, SVM
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Hardware Requirements:
Processor - I3/Intel Processor
Hard Disk - 160GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
RAM - 8GB
Software Requirements:
Operating System : Windows 7/8/10
Server side Script : HTML, CSS, Bootstrap & JS
Programming Language : Python
Libraries : django, Pandas, Smtplib, Numpy
IDE/Workbench : PyCharm
Technology : Python 3.6+