Azoft RnDCase Studies

Research and Development

Azoft R&D department handles the most challenging, non-standard issues that arise when implementing software solutions. Many of the problems tackled by our R&D team strongly rely on scientific research and may involve technical risks. If you have an idea or a technologically complex project but aren't sure how to make it work, Azoft R&D team can study the problem and come up with a technologically sound approach. In this section you can see some of the projects we have recently completed.

Developing Barcode Scanner Mobile Application for iOS

By Ozhiganov Ivan on February 18, 2013
Our R&D team recently developed a framework for a barcode-scanning application for iOS devices. The requirements stated that this application should be able to scan blurry barcodes that are aligned in any direction without sacrificing the app’s performance. In other words, the user shouldn’t have to align the barcode along the horizontal axis.

Such application requires lots of image processing and therefore relies on a large volume of mathematical calculations. Therefore, we decided to make use of the GPU and divide the process into two main stages. The first stage is to process the image captured by the mobile camera and determine which area is the barcode. The second stage is to read and decoding the barcode.

Hydrodynamic Process Simulation on a Mobile Device

By Ozhiganov Ivan on February 17, 2013
Our R&D team developed a framework for imitating paint dispersion on the surface of water on an iPad. The project involved two main challenges. First, was to come up with an algorithm that provides the most realistic imitation of paint dispersion. The second challenge was to perform calculations on an iPad, taking into consideration its limitations compared to a PC.

Initially, we relied on the Lattice Boltzmann methods in order to simulate fluid dynamics. The experience we gained while working with Lattice Boltzmann methods helped us come up with another algorithm based on Navier-Stokes equations and Kubelka-Munk compositing model. We applied the resulting algorithm for the development of AquaReal app that imitates watercolor painting on an iPad, as well as WaterHockey game. We are currently working on another application that imitates Turkish art of aqueous surface design called Ebru.

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