An automatic segmentation algorithm that is based on watersheds and region merging type multi-scale segmentation (MSS) is proposed, which can be used as the initial step of an object-based classifier. First, the image is segmented using watershed segmentation. Then, primitive segments are merged to create meaningful objects by the proposed hybrid region merging algorithm. During these steps, an unsupervised segmentation accuracy metric is considered so that best performing parameters of the proposed algorithm are determined automatically. By this way, the proposed segmentation algorithm has become fully automatic. Experiments are done on images taken from Google Earth (R) software. Algorithm performance is computed using the ground truths of these images. Also, results for some other Google Earth (R) images are presented for qualitative performance assessment.