A　method　is　presented　to　automatically　extract　and　analyze　positive　cells　in　tumor　immunohistochemical　pathology　images　based　on　the　YCbCr　color　space.　First,　according　to　the　distribution　rules　of　positive　cells　in　the　YCbCr　space,　it　uses　the　components　of　Y,　Cb,　and　Cr　as　threshold　conditions　and　leverages　the　maximal　entropy　principle　to　build　a　model　to　segment　and　extract　positive　cells.　Then,　it　extracts　the　characteristic　parameters　for　positive　cell　regions.　Finally,　it　quantitatively　analyzes　the　key　parameters　for　positive　cells,　such　as　density　and　intensity.　The　experimental　results　showed　that　the　method　can　be　further　extended　to　immunohistochemical　standardization.