Name
Abstract | ||
|---|---|---|
Image segmentation is a broad area, which covers strategies for splitting one input image into its components. This paper aims to present a re-segmentation approach applied to urban imagery, where the interest elements (houses roofs) are considered to have a rectangular shape. Our technique finds and generates rectangular objects, leaving the remaining objects as background. With an over-segmented image we connect adjacent objects in a graph structure, known as Region Adjacency Graph - RAG. We then go into the graph, searching for best cuts that may result in segments more rectangular, in a relaxation-like approach. Graph search considers information about object class, through a pre-classification stage using Self-Organizing Maps algorithm. Results show that the method was able to find rectangular elements, according user-defined parameters, such as maximum levels of graph searching and minimum degree of rectangularity for interest objects. |
Year | Venue | Keywords |
|---|---|---|
2009 | VISAPP 2009: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2 | Re-Segmentation, Graph-Based Segmentation, Remote Sensing, Urban Imagery |
Field | DocType | Citations |
Adjacency list,Computer vision,Graph,Pattern recognition,Segmentation,Computer science,Image segmentation,Object Class,Artificial intelligence | Conference | 1 |
PageRank | References | Authors |
0.35 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thales Sehn Korting | 1 | 24 | 12.47 |
| Luciano Vieira Dutra | 2 | 71 | 26.78 |
| Leila Maria Garcia Fonseca | 3 | 47 | 17.89 |