Segmentation of Dashboard Screen Images: Preparation of Inputs for Object-based Metrics of UI Quality

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU131386" target="_blank" >RIV/00216305:26230/19:PU131386 - isvavai.cz</a>

Result on the web

<a href="https://www.fit.vut.cz/research/publication/11878/" target="_blank" >https://www.fit.vut.cz/research/publication/11878/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0007312301990207" target="_blank" >10.5220/0007312301990207</a>

Result language

angličtina

Original language name

Segmentation of Dashboard Screen Images: Preparation of Inputs for Object-based Metrics of UI Quality

Original language description

Using object-based metrics to analyse design aspects of user interfaces (UI) is a suitable approach for the quantitative evaluation of the visual quality of the user interfaces. Balance or Symmetry are examples of such metrics. On the other hand, we need to deal with the problem of the detection of objects within a user interface screen which represent the inputs for the object-based metrics. Todays user interfaces (e. g., dashboards) are complex. They consist of several colour layers, and it is complicated to segment them by well-known page segmentation methods which are usually used for the segmentation of printed documents. We also need to consider the subjective perception of users and principles of objects grouping (as Gestalt laws). Users usually group simple objects (graphical elements and shapes) into coherent visually dominant objects. We analysed the experience of 251 users manually segmenting the dashboard screens to design a novel method for the segmentation of dashboard screen images. The method initially focuses on the reduction of image colours which represents image layers. Then, it detects the primitives which creates a screen layout. Finally, the method processes the screen layout using the combination of the top-down and bottom-up segmentation strategy and detects visually dominant regions.

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

ISBN

978-989-758-354-4

ISSN

—

e-ISSN

—

Number of pages

9

Pages from-to

199-207

Publisher name

SciTePress - Science and Technology Publications

Place of publication

Prague

Event location

Prague

Event date

Feb 25, 2019

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

000668124000017