摘要
为克服传统以像素为单位的随机游走算法随着像素点增多,计算量大、复杂度高、分割速度大大减慢,且对彩色图像分割效果不理想的问题,提出一种改进的随机游走图像分割方法。首先,使用改进和优化后的分水岭算法对目标图像进行预分割,为防止分水岭算法过分割问题,结合使用非线性各向异性扩散方法和形态学处理方法进行处理;然后,将分水岭算法分割后形成的同质区域作为图的节点用于随机游走算法,通过用户标记种子区域,分割出感兴趣的目标物体;最后,给出传统随机游走分割方法与本文提出的分割方法的实验结果比较,并对它们进行分析和评价。
An improved random walk algorithm for image segmentation is proposed to solve the problems of heavy computation and complex, a very slow speed with the increase of pixels and unreliable segmentation performance to color image of the traditional random walk algorithm for image segmentation in pixel. First, an improved and optimized watershed transform is used to partition the image into many small homogeneous region pieces. In order to avoid over-segmentation problem of watershed, the image is preprocessed with nonlinear anisotropic diffusion smooth algorithm morphologie processing; secondly, the graph based on region is build on the homogeneous region pieces pre-segmented by watershed transform and used as graph vertexes of random walk algo- rithm. Then, the target object interested is segmented out following the user guidance to segment the object. Finally, some exper- imental results are conducted to compare, analyze and evaluate the performance of traditional random walk and the new proposed algorithm. A conclusion and future development is made in the end.
出处
《计算机与现代化》
2013年第8期1-6,共6页
Computer and Modernization
基金
国家自然科学基金资助项目(61175004)
北京市自然科学基金资助项目(4112009)
北京市教委科技发展重点项目(KZ01210005007)
高等学校博士学科点专项科研基金资助项目(20121103110029)
关键词
随机游走
分水岭
各向异性扩散
形态学处理
random walk
watershed
anisotropic diffusion
morphologic processing
作者简介
王梅（1987-），女，甘肃武威人，北京工业大学计算机学院硕士研究生，研究方向：图像处理，模式识别
李玉鑑（1968-），男，湖南邵东人，教授，博士生导师，CCF高级会员，研究方向：模式识别，机器学习和人工智能。
