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OCR application
Giuliano De Sabata
An 4 CTI
Description
● An OCR application performs a conversion
between printed text (png, jpg, pdf) to a
standard ASCII stream of characters.
● We want to create an application that will
recognize latin characters in a wide variety of
fonts, and in different sizes, lighting
condidtions and skew.
Resources
● We need a small team that can work in an
agile manner, possibly interchanging roles
beteen them:
●
Resources
● Estimated number of work hours for each role
● Project manager: 4 hours
● Preprocessing development: 6 h
● Neural net developer: 10 h
● Testing: 1 hour
Project planning
Design phase
● Requirements for a running application have to be set: range of
character size, type of images to be processed, minimum percentage
of correct recognition.
● The implementation language and libraries have to be decided;
● Main data structures and control flow have to be designed
● The team of three can perform a meeting to adress each of the
issues on the agenda
● https://docs.google.com/document/d/1EVlFmJXdYjszBd4y17rPHfXa
Y31MDLrbwLv05uBFFaQ/edit
Development phase
● There are two parts of the net that can be
implmented in parallel:
● The preprocessing functionality focuses on
bringing each character at roughly the same
size and color palette
● The neural network algorithm is a generic
machine learning method for a classification
problem; Implementation and validation can
be made independentley;
Open Project
● Given detailed task estimations and task
dependencies, Open Project shows a project
schedule of around 14 days.
● We can see the workflow of all activities and
how each member can be productive at each
moment (if possible);
Workflow
Conclusions
● The Open Project tool allows project
managers and team members to have a
perspective over the time needed to
implement a project and the current status of
the implementation.

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Pres msp

  • 1. OCR application Giuliano De Sabata An 4 CTI
  • 2. Description ● An OCR application performs a conversion between printed text (png, jpg, pdf) to a standard ASCII stream of characters. ● We want to create an application that will recognize latin characters in a wide variety of fonts, and in different sizes, lighting condidtions and skew.
  • 3. Resources ● We need a small team that can work in an agile manner, possibly interchanging roles beteen them: ●
  • 4. Resources ● Estimated number of work hours for each role ● Project manager: 4 hours ● Preprocessing development: 6 h ● Neural net developer: 10 h ● Testing: 1 hour
  • 6. Design phase ● Requirements for a running application have to be set: range of character size, type of images to be processed, minimum percentage of correct recognition. ● The implementation language and libraries have to be decided; ● Main data structures and control flow have to be designed ● The team of three can perform a meeting to adress each of the issues on the agenda ● https://docs.google.com/document/d/1EVlFmJXdYjszBd4y17rPHfXa Y31MDLrbwLv05uBFFaQ/edit
  • 7. Development phase ● There are two parts of the net that can be implmented in parallel: ● The preprocessing functionality focuses on bringing each character at roughly the same size and color palette ● The neural network algorithm is a generic machine learning method for a classification problem; Implementation and validation can be made independentley;
  • 8. Open Project ● Given detailed task estimations and task dependencies, Open Project shows a project schedule of around 14 days. ● We can see the workflow of all activities and how each member can be productive at each moment (if possible);
  • 10. Conclusions ● The Open Project tool allows project managers and team members to have a perspective over the time needed to implement a project and the current status of the implementation.