基于鲁棒随机游走的交互式植物叶片分割

Interactive Leaf Segmentation Using Robust Random Walk

受背景、阴影和反射等不同成像环境影响,固定模型难以解决植物叶片分割问题.针对此情况,文中提出基于鲁棒随机游走的交互式植物叶片分割方法,采用交互式策略对用户指定像素先验信息进行传播,通过鲁棒随机游走算法实现植物叶片分割.首先,基于随机游走算法构建成对像素的关系,建立一个超像素一致性约束模型,促使分割图像边缘更光滑.然后,通过人机交互获取指定像素先验信息.最后,利用对数似然比预测像素属于背景的概率,并用于指导标签传播.在宽松受控和非受控环境植物叶片图像上的实验表明,文中方法可以更好地得到光滑、鲁棒的植物叶片分割图.

Segmenting the plant leaf by a fixed model is problematic due to different imaging conditions, such as backgrounds, shadows and reflections. In this paper, interactive plant leaf segmentation method based on robust random walk is proposed. The interactive strategy is employed to propagate prior information of user-specified pixel, and robust random walk algorithm is used to realize plant leaf segmentation. The relationship of pairwise pixels is considered based on random walk and a super-pixel-consistent constraint is added to make the edges of segmentation smooth. Since the random walk algorithm only considers pairwise pixel relations, it is sensitive to the specified and connected pixels. The prior information of specified pixel is obtained through human-machine interaction. On the basis of random walk model, a log-likelihood ratio is used to predict the probability of a pixel belonging to the background and guide the label propagation. Experiments on plant leaf images in loose controlled and uncontrolled environments show that the proposed method obtains smoother and more robust plant leaf segmentation images than other methods.