k-max - Segmentation based on selection of Max-tree deep nodes

摘要

This work proposes the segmentation of grayscale image from of its hierarchical region based representation. The Max-tree structure has demonstrated to be useful for this purpose, offering a semantic vision of the image, therefore, reducing the number of elements to process in relation to the pixel based representation. In this way, a particular searching in this tree can be used to determine regions of interest with lesser computational effort. A generic application of detection of peaks is proposed through searching nodes to k_(up) steps from leaves in the Max-tree (this operator will be called k-max), being each node corresponds to a connected component. The results are compared with the optimal thresholding and the H-maxima technique.