Algorithm for Mapping Layout Grids in User Interfaces: Automating the “Squint Test”

Abstract

Human-Computer Interaction sees increased application of AI methods, particularly for testing and assessing the characteristics of graphic user interfaces (UIs). For instance, target users’ subjective perceptions of visual complexity, aesthetic impression, trust, etc. can be predicted to some extend based on UI appearance. Buttons, text blocks, images and other elements in today’s UIs at all platforms are usually aligned to grids – i.e. regular vertical and horizontal lines – in order to decrease visual clutter. However, the grids are not apparent in the UI representations available for analysis (HTML/CSS, etc.), unlike in design mockups, and have to be reverse-engineered for the benefit of further UI assessment. In our paper we propose the algorithm for automated construction of layout grids on top of visual representations (screenshots) of existing UIs and demonstrate its work with various configuration parameters. The algorithm was inspired by the informal Squint Test known from Usability Engineering practice and is based on subsequent application of several computer vision techniques supported by OpenCV library. The main stages are edge detection, image pixelization, grid overlaying, and cell coding. The tuning of the algorithm’s configuration parameters can be performed to match the UI perception by representative users, as demonstrated in the paper. The outcome of the algorithm is a coded representation of graphical UI as a 2D matrix, which is a convenient medium for further processing. The automation of UI layouts coding can allow obtaining large datasets needed by up-to-date user behavior models that predict the quality of interaction with UIs.