符合人类视觉感知的图像对象分割方法

Image Object Segmentation Method in Accord with Human Vision Perception

提出一种符合人类视觉感知的图像对象分割方法,包括双尺度的区域分割和基于模型的对象提取。运用非线性尺度算子对图像进行大尺度平滑,结合颜色量化和视觉一致性的颜色聚类完成图像的粗分割。在原尺度上融合区域的纹理、颜色信息对分割区域进行区域合并,并利用对象模型完成图像对象的提取。实验结果表明,该算法的分割结果符合人类视觉感知特性,能够较好地完成图像对象分割。

Image object segmentation method in accord with human vision perception, which consists of double-scale region segmentation and object extraction based on object model, is proposed in this paper. An image is smoothed by nolinear scale operator in coarse-scale, color quantization and perceptual color clustering are exploited to form the initial segmented regions. The initial regions are merged based on the region distance in the original finest-scale. Object model is used to implement image object extraction. Experimental results demonstrate that the proposed algorithm gets better image object segmentation with favorable consistency to human vision perception.