This　paper　proposes　a　general-purpose　no-reference　image　quality　assessment　(NR-IQA)　method　that　investigates　the　image＇s　structure　information　from　a　new　aspect,　i.e.,　the　characteristic　of　image　edge　profiles　that　depict　the　directional　property　of　adjacent　edge　points　in　the　spatial　domain　of　the　image.　More　specifically,　we　extracted　the　image＇s　edge　map　based　on　Laplacian　of　Gaussian　(LoG)　filtration　and　zero-crossing　(ZC)　detection　and　refined　the　edge　map　to　be　1-pixel　wide.　We　then　explored　the　edge　map　by　investigating　edge　profiles＇　statistics　in　a　local　window　with　a　5　x　5-pixel　size.　Considering　the　consensus　that　natural　images　consist　of　directional　structures,　we　found　that　the　spatial　distribution　property　of　adjacent　edge　points　can　be　represented　through　several　edge　profiles　called　edge　patterns,　which　are　selected　from　natural　images　with　a　proposed　smooth　criterion.　With　the　proposed　edge　patterns　and　their　statistical　histogram　for　the　image　and　the　support　vector　regression　technique,　we　proposed　the　NR-IQA　model　based　on　the　edge　patterns　in　the　spatial　domain,　named　EPISD.　The　proposed　method　has　been　extensively　validated　on　the　LIVE,　CSIQ,　TID2013,　MDID2017,　SIQAD,　and　SCID　databases.　The　experimental　results　showed　that　EPISD　has　a　competitive　performance　with　state-of-the-art　methods　and　works　stably　across　different　databases.