A　CapsNet-based　Chinese　character　font　representation　model　is　proposed　to　represent　Chinese　character　font　by　the　representation　of　components.　Firstly,　representative　vectors　of　all　categories　are　generated　by　the　model.　Then,　a　group　of　component　representative　vectors　are　selected　by　the　Euclidean-distance-based　outlier　detection　according　to　component　probabilities.　Finally,　these　vectors　are　utilized　to　form　the　Chinese　character　font　representations.　The　experimental　results　show　that　the　proposed　model,　merely　trained　on　component　fonts,　is　capable　of　identifying　components　of　Chinese　characters　and　automatically　generating　effective　representation　of　Chinese　characters.　©　2019,　Science　Press.　All　right　reserved.