Webpage cross-browser test from image level

Abstract

Incompatibility of webpages under different browsers and platforms is a typical technical obstruction for webpage design. To address this issue, a key challenge is to automatically detect the incompatible components and quantitatively assess the distortion extent in cross-browser tests. This paper presents a new algorithm for image pair comparison from webpages, called iterative perceptual hash (IPH), as well as a new distortion evaluation index called structure-color-saliency (SCS). The IPH that operates in an iterative manner is proposed to detect content changes considering both global structure and local content difference. The SCS assesses the distortion extent in both dimensions of image structure and color and is capable of imitating the nonlinear human perception. Experiment results demonstrate the effectiveness of IPH (e.g., F1-score 96%) and the high consistency of SCS with subjective results.