A　segmentation　method　based　on　greedy　snake　algorithm　and　radical　recognition　was　proposed　to　solve　the　problems　of　interlacing,　adhesion　and　over-segmentation　of　Chinese　handwritten　text.　Firstly,　the　original　text　segmentation　trajectory　was　established　based　on　the　greedy　snake　algorithm,　and　the　segmentation　path　was　optimized　according　to　the　multiple　rules.　Then,　candidate　adhesion　points　were　extracted　based　on　the　outline　and　skeleton　of　adhesion　characters,　and　the　gluttonous　snake　algorithm　was　used　for　secondary　segmentation.　Finally,　the　radical　extraction　and　recognition　of　the　over-segmentation　characters　was　carried　out,　and　the　merging　direction　was　determined　based　on　the　structure　of　Chinese　characters.　Combined　with　geometric　confidence　and　recognition　confidence,　the　merging　of　the　over-segmentation　characters　was　completed,　and　the　correct　text　segmentation　result　was　finally　obtained.　The　effectiveness　of　the　algorithm　was　verified　by　the　experiment　on　1542　lines　of　handwritten　text　from　a　high　school　test　papers　of　Shaanxi　province.　The　result　shows　that　the　accuracy　of　the　segmentation　algorithm　can　reach　82.　15%.　©　2022,　Editorial　Department,　Journal　of　South　China　University　of　Technology.　All　right　reserved.