A　new　approach　for　color　image　segmentation　is　proposed　based　on　Kuramoto　model　in　this　paper.　Firstly,　the　classic　Kuramoto　model　which　describes　a　global　coupled　oscillator　network　is　changed　to　be　one　that　is　locally　coupled　to　simulate　the　neuron　activity　in　visual　cortex　and　to　describe　the　influence　for　phase　changing　by　external　stimuli.　Secondly,　a　rebuilt　method　of　coupled　neuron　activities　is　proposed　by　introducing　and　computing　instantaneous　frequency.　Three　oscillating　curves　corresponding　to　the　pixel　values　of　R,　G,　B　for　color　image　are　formed　by　the　coupled　network　and　are　added　up　to　produce　the　superposition　of　oscillation.　Finally,　color　images　are　segmented　according　to　the　synchronization　of　the　oscillating　superposition　by　extracting　and　checking　the　frequency　of　the　oscillating　curves.　The　performance　is　compared　with　that　from　other　representative　segmentation　approaches.