Although　there　are　many　independent　studies　on　the　detection　of　white　blood　cell　or　classification　of　white　blood　cell,　few　papers　have　taken　them　into　consideration.　This　study　proposed　a　method　for　recognizing　five　types　of　leukocytes　based　on　multi-scale　regional　growth　and　mean-shift　clustering.　The　key　idea　of　the　proposed　method　is　to　extract　texture　features　of　leukocytes　in　a　visual　manner.　And　it　is　a　non-parametric　texture　features　extracting　method　different　from　traditional　algorithms.　Finally,　SVM (Support　Vector　Machine)　is　used　for　classification.　Some　leukocyte　images　were　used　and　the　overall　correct　recognition　rate　reached　97.96%,　indicating　the　feasibility　and　robustness　of　the　proposed　method.　©　The　Author(s)　2018.