Image Segmentation Using Component Tree and Normalized Cut

Combining Hierarchical Structures on Graphs and Normalized Cut for Image Segmentation

“…The goal of these experiments is to compare the techniques for building the similarity graph based on Pixel Grid (Shi & Malik, 2000), Multiscale Pixel Grid (Cour et al, 2005), Quadtree , and Component Tree (Carvalho, Costa, Ferreira & Cesar-Jr., 2010). Fig.…”

“…In the next subsections we present some fundamental concepts on graphs, and four image-graph representation approaches: based on the Pixel Grid (Shi & Malik, 2000) , Multiscale Pixel Grid (Cour et al, 2005), based on the Component Tree (Carvalho, Costa, Ferreira & Cesar-Jr., 2010), and based on the Quadtree . Approaches based on the Component Tree, Quadtree,andMultiscale Pixel Grid rely on hierarchical structures to model an image as a graph, and provide different segmentation results when compared to the classical non-hierarchical pixel grid approach.…”

“…The Component Tree (CT) (Carvalho, Costa, Ferreira & Cesar-Jr., 2010) is a hierarchical representation of a digital image after thresholding operations between its minimum and maximum gray values (Mosorov & Kowalski, 2002). There exists a relation of inclusion between components at sequential gray levels in the image, explained below by the partition definition (Carvalho, 2004).…”

“…Monteiro & Campilho (2008) proposed the Watershed Normalized Cut, which uses the regions from the Watershed image segmentation as nodes for the similarity graph. The Watershed region similarity graph is either used by Carvalho et al (2009) for comparison with the primitive pixel affinity graph in yeast cells images segmentation. Ma & Wan (2008) used Watershed based similarity graphs to segment texture images.…”

“…In fact, these components can provide more relevant information in particular cases. Therefore, we have defined the Reverse Component Tree (RCT) (Carvalho, Costa, Ferreira & Cesar-Jr., 2010) where two connected components…”