Automatic road area extraction from printed maps based on linear feature detection

Sebastien Callier, Hideo Saito

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Raster maps are widely available in the everyday life, and can contain a huge amount of information of any kind using labels, pictograms, or color code e.g. However, it is not an easy task to extract roads from those maps due to those overlapping features. In this paper, we focus on an automated method to extract roads by using linear features detection to search for seed points having a high probability to belong to roads. Those linear features are lines of pixels of homogenous color in each direction around each pixel. After that, the seeds are then expanded before choosing to keep or to discard the extracted element. Because this method is not mainly based on color segmentation, it is also suitable for handwritten maps for example. The experimental results demonstrate that in most cases our method gives results similar to usual methods without needing any previous data or user input, but do need some knowledge on the target maps; and does work with handwritten maps if drawn following some basic rules whereas usual methods fail.

Original languageEnglish
Pages (from-to)1758-1765
Number of pages8
JournalIEICE Transactions on Information and Systems
Issue number7
Publication statusPublished - 2012 Jul


  • Image segmentation
  • Raster map
  • Road extraction

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence


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