Novel MSER-guided street extraction from satellite images

Ehab Salahat, Hani Saleh, Andrzej Sluzek, Baker Mohammad, Mahmoud Al-Qutayri, Mohammad Ismail

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

The paper presents a novel technique to segment and extract streets from satellite images. This technique utilizes, for the first time in the known literature, the Maximally Stable Extremal Regions (MSER) algorithm to robustly identify and segment streets from satellite images. The technique extracts dark MSERs and then classifies them based on multiple metrics such as the intensity of the pixels, the region stability, and the major-to-minor axes ratio. Testing results under multiple scenarios corroborate the accuracy of the proposed technique. The technique will allow fast and accurate implementation of a wide spectrum of applications such as in Global Positioning System (GPS) driving guidance.

Original languageBritish English
Title of host publication2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1032-1035
Number of pages4
ISBN (Electronic)9781479979295
DOIs
StatePublished - 10 Nov 2015
EventIEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Milan, Italy
Duration: 26 Jul 201531 Jul 2015

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2015-November

Conference

ConferenceIEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Country/TerritoryItaly
CityMilan
Period26/07/1531/07/15

Keywords

  • Image Processing
  • Maximally Stable Extremal Regions
  • Segmentation
  • Street Extraction

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