With　the　quick　development　and　popularity　of　computers,　computer-generated　signals　have　drastically　invaded　into　our　daily　lives.　Screen　content　image　is　a　typical　example,　since　it　also　includes　graphic　and　textual　images　as　components　as　compared　with　natural　scene　images　which　have　been　deeply　explored,　and　thus　screen　content　image　has　posed　novel　challenges　to　current　researches,　such　as　compression,　transmission,　display,　quality　assessment,　and　more.　In　this　paper,　we　focus　our　attention　on　evaluating　the　quality　of　screen　content　images　based　on　the　analysis　of　structural　variation,　which　is　caused　by　compression,　transmission,　and　more.　We　classify　structures　into　global　and　local　structures,　which　correspond　to　basic　and　detailed　perceptions　of　humans,　respectively.　The　characteristics　of　graphic　and　textual　images,　e.g.,　limited　color　variations,　and　the　human　visual　system　are　taken　into　consideration.　Based　on　these　concerns,　we　systematically　combine　the　measurements　of　variations　in　the　above-stated　two　types　of　structures　to　yield　the　final　quality　estimation　of　screen　content　images.　Thorough　experiments　are　conducted　on　three　screen　content　image　quality　databases,　in　which　the　images　are　corrupted　during　capturing,　compression,　transmission,　etc.　Results　demonstrate　the　superiority　of　our　proposed　quality　model　as　compared　with　state-of-the-art　relevant　methods.