ppt

1. HAND WRITING RECOGNITION SYSTEM
Presentation By:
GAUTAM JAIN
VIPUL JAIN
VAIBHAV UPRETI

2. ABSTRACT
The aim of this project is to use this opportunity given
by our teacher to comprehend latest concepts of
machine learning and artificial intelligence by
designing a working prototype of a handwriting
recognition system. Considering the various types of
recognition systems, we decided to draw our
inspiration from tech innovations like Google lens and
Samsung's Bixby vision which recognize scanned texts
and images and show to their users results based on it.

3. PROJECT DEVELOPMENT
There are three main stages of development in our
project:
Pre-processing&
Data
Segmentation
Data
Recognition
Deployment of
model

4. Control Flow Diagram for HCR System

5. TECH STACK
The Tech Stack of our prototype system involves:
• YOLO Algorithm
• CTC Word Beam Search
• Simple HTR
• Linux Server

6. PRE-PROCESSING & DATA SEGMENTATION
Sequence Diagram of Pre-processing Sequence Diagram of Segmentation
Line Segmentation
Word Segmentation

7. DATA RECOGNITION
Sequence Diagram of Feature Extraction
Sequence Diagram of Classification
DFD(level 1) for Recognition Unit

8. DEPLOYMENT OF THE MODEL
Deployment Diagram

9. CHALLENGES
Some of the most crucial challenges faced during the
creation of the model were:
• Setting up the correct environment & packages after
matching dependencies of all libraries
• Running script asynchronously as a background job to
optimize queries
• Fix recursive layer calling of RNN layers

10. CONCLUSION & FUTURE SCOPE
• This work further extended to the character recognition for other
languages.
• It can be used to convert the fax and news papers into text format.
• In order to recognize words, sentences or paragraphs we can use
multiple ANN for classification.
• It can be used in post office for reading postal address.
• Many regional languages throughout world have different writing
styles which can be recognized with HCR systems using proper
algorithm and strategies