User interactive object extraction with sequential image segmentation

In this study, a graph-based image segmentation algorithm which was developed in recent years and achieves a significant success in terms of the performance of both the accuracy and speed is used as an intermediate process for a user interactive object extraction method. In the object extraction method developed, the related image is subdivided into segments and, then, these segments are merged according to their label values by using the area determined by the user at first. The image segmentation algorithm used in the scope of this work fulfills a sequential segmentation process on the one dimensional edge array of Prim's minimum spanning tree representation. The algorithm does the segmentation by cutting the specified edges on the tree. According to the method developed, these cut edges are kept and some of them are added to the tree again in the merging stage; so that, the segments at the ends of the edge added are merged. Owing to this process, the process of finding the least weighted edge between the two segments to be merged, which needs to be performed before the merging stage according to the previous studies, is not needed. The method developed here is compared with some methods in the literature on a dataset consist of real life images, and it seems that the method shows a significant superiority to the other methods.