Skip to main navigation Skip to search Skip to main content

SIFT based automatic ROI localization and designation

  • Xi'an Jiaotong University

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

Abstract

There is a rapid increase of remote sensing images in the repositories. While for certain purposes, we just need the region of interest (ROI). In this paper, SIFT is applied for feature extraction, descriptor generation and point matching with strict criterions to locate ROI. With the robust matching pairs of points, a simple approach for computing scale, rotation and translation separately is proposed. To solve the parameters, we introduce an improved RANSAC algorithm with two cost functions to achieve rapid computation efficiency. The method for ROI localization and designation performs great in a series of experiments and satisfying results can be seen.

Original languageEnglish
Title of host publicationMIPPR 2007
Subtitle of host publicationRemote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications
DOIs
StatePublished - 2007
EventMIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications - Wuhan, China
Duration: 15 Nov 200717 Nov 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6790
ISSN (Print)0277-786X

Conference

ConferenceMIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications
Country/TerritoryChina
CityWuhan
Period15/11/0717/11/07

Keywords

  • Improved RANSAC
  • ROI
  • SIFT
  • Transformation parameters

Fingerprint

Dive into the research topics of 'SIFT based automatic ROI localization and designation'. Together they form a unique fingerprint.

Cite this