Automating the process of data entry and manipulation

1. Smart Shutter
Group Members:
• Mohammed Zain ul Abdeen 12627
• Javaria Junaid 13014
• Mustafa Poonjla 13220

2. Introduction
Automating the process of data entry and
manipulation
Computer vision is an interdisciplinary scientific
field that deals with how computers can gain
high-level understanding from digital images
Supervisor:
Saiyed Shahab Ahmed

3. About Digital Processing System (DPS)
Innovative Information: Bringing
information technology solutions to
diverse portfolio of customers.
Solutions: Provide high-end
technical solutions to customers in
telecommunication finance,
aviation, etc.
Expertise: Presentations are tools
that can be demonstrations.
Training and Consultancy

4. Problem Statement
• Lack of information about importance of digitization
• Extracting data through manual search is time consuming
• Difficult to maintain all manual data
• Digitization will allow to integrate conventional records
into digital form
• It will help in cost saving, data redundancy and will prevent
from human error
• It will save time

5. About the Product
• Created a web Application that helps user to upload forms and get their data extracted
according to there requirement.
Main features:
• Image pre-processing
• Feature Extraction
• Data tagging
• Document's data processing
• Data Management

6. Use Cases • Financial Services: : It will help bank and financial institutions
to transform incoming documents into actionable data
• Health care: can help with patient registration by streamlining
the process of collecting, entering, and verifying patient and
insurance data
• Government Institutions: can use it to process contracts,
surveys, census forms, voting ballots, pension cards, tax
declarations, social applications.
• Educational Institutes: can use it for the management of
documents including test, examination, reports, transcripts or
letter of reference.
• Airlines: could use it for automating the boarding the process
of the passengers by extracting the relevant data from
passports and tickets.

7. How we made the App
• First we read and understood the product requirements provided to
us by D.P.S.
• We researched on the approaches that were followed in the similar
projects previosuly.
• Accuire relevant data.
• Image preprocessing.
• Feature extraction
• Data Tagging/vizualization/management.
• Front End development and deployment.

8. Web Application Demo
• Show demo

9. Future Work
Deep learning: Deep learning methods can achieve state-of-the-art
results on challenging computer vision problems such as image
classification and object detection.
Will work on improving efficiency