Automatic Image Segmentation Based on Maximal Similarity Based Region Merging

Image segmentation is one of the most significant tasks in computer vision. Since automatic techniques are hard for this purpose, a number of interactive techniques are used for image segmentation. The result of these techniques largely depends on user feedback. It is difficult to get good interactions for large databases. On the other hand, automatic image segmentation is becoming a significant objective in computer vision and image analysis. We propose an automatic framework to detect foreground. We are applying Maximal Similarity Based Region Merging (MSRM) technique for region merging and using image boundary to identify foreground regions. The results confirm the effectiveness of the proposed framework. The proposed framework reveals its effectiveness especially to extract multiple objects from background.