Template Patch Driven Image Segmentation

We present a method that partitions a single image into two layers, requiring that one layer has similar properties in terms of pixel colour variation to a provided template patch. First, the paper provides a new view on defining a similarity function for a pixel with its small neighbourhood to be part of the texture described by the template patch. This results in better description of pixels near the texture boundary. Second, it is shown how the Maximally Stable Extremal Regions (MSERs), originally designed for wide baseline stereo matching, can be used to locally merge pixels having the same intensity and thus reduce the dimension of the graph representing the image. The MSERs help in texture description and yield significant reduction of memory and computation time. Finally the graph is fed into the min.cut/max.flow algorithm to cut the graph into two parts. Performance of the method is presented on some images from the Berkeley database. Finally, restrictions in using the method are discussed.