Semi-automated road detection from high resolution satellite images by directional morphological enhancement and segmentation techniques

D. Chaudhuri, N. K. Kushwaha, A. Samal

Research output: Contribution to journalArticlepeer-review

146 Scopus citations

Abstract

Extraction of map objects such roads, rivers and buildings from high resolution satellite imagery is an important task in many civilian and military applications. We present a semi-automatic approach for road detection that achieves high accuracy and efficiency. This method exploits the properties of road segments to develop customized operators to accurately derive the road segments. The customized operators include directional morphological enhancement, directional segmentation and thinning. We have systematically evaluated the algorithm on a variety of images from IKONOS, QuickBird, CARTOSAT-2A satellites and carefully compared it with the techniques presented in literature. The results demonstrate that the algorithm proposed is both accurate and efficient.

Original languageEnglish (US)
Article number6227311
Pages (from-to)1538-1544
Number of pages7
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume5
Issue number5
DOIs
StatePublished - 2012

Keywords

  • Enhancement
  • morphology
  • remote sensing
  • resolution
  • road detection
  • segmentation

ASJC Scopus subject areas

  • Computers in Earth Sciences
  • Atmospheric Science

Fingerprint

Dive into the research topics of 'Semi-automated road detection from high resolution satellite images by directional morphological enhancement and segmentation techniques'. Together they form a unique fingerprint.

Cite this