本文研究了典型的基于區(qū)域的圖像分割方法主動(dòng)形狀模型（Active Shape Model, ASM）和基于邊緣的圖像分割snake 算法，分析了算法適用條件和各自的優(yōu)缺點(diǎn)。結(jié)合snake 模型與主動(dòng)形狀模型，提出了一種基于多級(jí)混合模型的圖像分割方法：首先使用ASM，獲得的對(duì)目標(biāo)圖像位置和形態(tài)的最佳估計(jì)，并通過(guò)snake 算法對(duì)匹配的結(jié)果進(jìn)行二次調(diào)整，獲取可以精確描述圖像邊緣信息的模型。試驗(yàn)表明了該方法的有效性。
關(guān)鍵字：主動(dòng)形狀模型；蛇模型；圖像分割

Abstract: Based on the analysis of Active Shape Model(ASM)and snake algorithm ,which gives us the application conditions and the advantages and disadvantages, A multistage hybrid matching method by integrating statistical model and snake is presented for image segmentation. A statistical model can locate objects rapidly, then a snake by adding an additional terms for the target object is built in order to consider the smoothness of the target contour.The method is well suited for automatic image segmentation.
Keywords: Active Shape Model; snake algorithm; image segmentation