Nonsubsampled contourlet transform is a new multi-scale multi-resolution powerful analysis tool. An unsupervised segmentation algorithm for color image is proposed based on nonsubsampled contourlet transform. Firstly, for nonsubsampled contourlet transform shift invariance, multi-scale edge is extracted in transform domain by using gradient vector method. Then, local low-frequency energy texture features and high-frequency multi-scale Zernike moments texture features are extracted from low-frequency sub-band and high-frequency sub-band in transform domain and fusing them. Finally, detecting seed points in edge map to represent color image regions, the region growing followed by region merging method is applied for segmentation by color and texture Euclidean distance. The experimental results show that the algorithm can automatically fulfill unsupervised segmentation for color image by combining color, multi-scale edge and texture properly, and has more precise and more robust segmentation effect than traditional algorithm.