摘要： 人物图像具有人体姿态的多样性、衣服颜色和纹理的各异性,存在噪声、低对比度、光照不均匀以及背景复等问题,以至于分割人物图像具有困难。为此,提出一种基于人脸检测和细胞自动机的全自动人物图像分割方法。用人脸检测算法识别人脸,得到面部轮廓。根据识别出的人脸位置建立目标和背景种子点估计模型,并得到目标和背景的种子点。采用细胞自动机进行像素标记任务,得到目标和背景两部分结果,实现全自动的人物图像分割。对分割数据集上不同类别的人物图像进行分割,实验结果表明,与Grabcut相比,提出的方法能自动和准确地对人物图像进行分割,并有效提高分割效率。

关键词: 人脸检测, 人物图像分割, 细胞自动机, 种子点估计模型, 分割评价

Abstract: Attributed to the diversity of human body posture,difference between clothing color and texture,the presence of noise,low contrast,uneven illumination and complex background,there are enormous difficulties with human image segmentation.So this paper proposes an automatic human image segmentation method based on face detection and Cellular Automata(CA).It uses face detection algorithm to recognize human faces and gets facial contours.Then it establishes object and background seed point estimation model based on the position of the detected face,and gets the object and background seed points.It performs pixel labeling task by cellular automata,and the image is divided into two parts of object and background.The method realizes fully automatic human image segmentation.Different kinds of human images are segmented over a segmentation database.Experimental results demonstrate that compared with Grabcut method,the proposed method can automatically and accurately segment the human images,and effectively improve the segmentation efficiency.

Key words: face detection, human image segmentation, Cellular Automata(CA), seed point estimation model, segmentation evaluation

中图分类号: 

• TP391.41