Prevas AB, a consulting company focused on industrial systems and  embedded systems, are looking to expand their mobile phone competency  and started two projects for this purpose. The rst is a diploma work to create a proof-of-concept barcode reader running on Symbian mobile phones, and the second is a student project for the new Innovative Programming bachelors degree to create a functioning price comparison application using IMS1 around the proof-of-concept created earlier. Both projects achieved their stated goals. However, due to none of the projects focusing on eciency or theoretical correctness the resulting application is dicult to start, runs slowly, leaks memory and is codewise bloated. These defects prevent the application from being realistically deployable, and a third project is started to clean up the application and improve it. This report describes the solutions employed in that third project The barcode reader in the application was split into two parts: First is the actual application written in C++ responsible for capturing images, sending them to the decoding server and displaying the result to the user. Second is  the decoding server, a separate application written in java that using a TCP-socket waits for images, decodes them, and returns the result. The primary goal of this project is to not only improve, but actually integrate the decoder into the C++ application, massively improving speed and memory usage. This report was written to highlight the lessons learned during this project, to describe the algorithms and methods used to improve the decoder and to be of use to anyone else writing time-constrained and heavily optimized barcode or pattern recognition code for Symbian devices.

This master thesis deals with the principles of form design, form printing and form processing. Three different types of forms and applications for their detection are created with the reference of these principles. This application provides to create a new type of form and to print out a form. The application itself is implemented in C++ with the use of OpenCV library. This work describes the classification methods of direction finding marks, identification numbers and submission numbers, bar codes EAN-13, page numbers, answer fields and single answers. The classification of all the handwritten numbers is implemented by neural nets.

This work deals with localization and decoding of the linear barcode EAN-13 in the image. It describes types and qualities of barcodes and pose posibble accesses into the localization and decoding. The practical part concerns with the concept and implementation of the algorithm having regard to effectiveness for processing in real time. The localization is established on finding similar features of the barcode among the read rows of the image and decoding is made by finding of the supreme conformity towards referential code figures.

The thesis describes the basic types of barcodes, their development and history. It's mentioned cutting barcodes by dimension, types of barcodes which are the best known and the best used, are described. The key chapter describes details of EAN-8, EAN-13, UPC-A and the additional symbol. It's outlined an algorithm for decoding barcode in image. In conclusion, the results are evaluated and a further development of the project is outlined.