Handwritten　text　recognition　is　mainly　used　in　text　input　technology,　which　plays　a　key　role　in　the　development　of　human-computer　interaction.To　address　the　lack　of　functionality　for　Chinese　and　English　mixed　handwritten　text　recognition　in　most　online　input　methods,　an　online　Chinese　and　English　mixed　handwritten　text　recognition　method　is　proposed.Through　the　integration　of　text　strokes　based　on　the　horizontal　relative　position,　vertical　overlap　rate,　area　overlap　rate　rules,　and　continuous　stroke　segmentation,　a　series　of　character　segments　are　obtained.In　addition,　Chinese　and　English　character　segments　are　classified　based　on　the　number　of　strokes,　aspect　ratio,　center　deviation,　smoothness,　and　recognition　confidence.On　this　basis,　according　to　the　classification　results,　combined　with　the　path　evaluation　of　the　natural-language　model　and　dynamic　programming　search　algorithm,　the　candidate　and　English　character　segments　are　combined　to　obtain　the　Chinese　and　English　character　sequences　to　be　recognized,　which　are,　respectively,　sent　to　the　Chinese　and　English　recognition　models　of　the　Convolutional　Neural　Network　(CNN)　to　obtain　the　handwritten　text　recognition　results.The　experimental　results　show　that　and　the　recognition　accuracy　of　the　online　handwritten　Chinese　and　English　mixed　text　is　93.67%,　the　proposed　method　can　segment　online　handwritten　Chinese　text　lines　as　well　as　online　handwritten　Chinese　and　English　text　lines　containing　characters.　©　2022,　Editorial　Office　of　Computer　Engineering.　All　rights　reserved.