Computer Generated Image Alterations Database

Modern user interfaces (UI) use animations and special effects to appear more interesting and appealing to consumers, such is the case for modern Set-Top-Boxes (STB). In order to provide their consumers with functional and reliable products, manufacturers are required to perform functionality verification (FV) of each product. Automated FV systems are becoming a prevailing method of FV due to manual FV becoming exceedingly time consuming as the devices become more complex. Generally, full reference (FR) image comparison between the device output image and the referent image is used in order to perform FV of device under test (DUT). Common methods for image comparison proved to be ineffective when comparing images captured from UIs containing animated objects or dynamic background. In order to provide manufacturers with high-end FV systems, it is necessary to develop new methods for image comparison capable of comparing images despite alterations caused by UI animations. Development of such algorithms requires large image databases which effectively simulate such image alterations. In this paper we present new Computer Generated Image Alterations Database (CGIAD) which contains 10000 test images with alterations caused by object transformations commonly used in UI animations (rotation, scaling, occlusion, and translation). CGIAD is freely available to the research community at http://www.rt-rk.com/other/CGIAD.html.