Raster Map Image Analysis

Raster map images (e.g., USGS) provide much information in digital form; however, the color assignments and pixel labels leave many serious ambiguities. A color histogram classification scheme is described, followed by the application of a tensor voting method to classify linear features in the map as well as intersections in linear feature networks. The major result is an excellent segmentation of roads, and road intersections are detected with about 93% recall and 66 % precision.

• Type: Conference
• Year: 2009
• Where: ICDAR
• Authors: Thomas C. Henderson, Trevor Linton
• Keywords: Color Histogram Classification, Document Analysis, ICDAR 2009, Linear Feature, Raster Map Images