Automatic tie-point matching using SURF-based image matching scheme

Jyun Ping Jhan, Jiann-Yeou Rau, Chien Chuan Lin, Yi Chen Shao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In digital photogrammetry, automatic tie-point matching is necessary for photo triangulation, integrated sensor orientation, epipolar image generation, image registration, image transformation, image stitching, surface modeling, etc. The objective for this research is to find out a cost-effective way to perform automatic tie-point matching in photo triangulation. SURF (Speed-Up Robust Features) is a scale and rotation invariant feature extraction operator that is suitable for feature point matching even a certain degree of geometrical distortion exists. In this paper, based on the SURF image matching scheme, we develop three tie-point matching strategies and a robust estimation filter to remove blunder error. In the meantime, multiple images measurement is considered to increase the redundancy and internal reliability during least-squares bundle adjustment. In the experiment, the performance of the developed tie-point matching scheme is evaluated by the posterior standard error (sigma0) of image coordinate measurement after free network bundle adjustment. Images acquired from different platforms and purposes are test, such as vertical aerial DSLR images in urban area, oblique aerial DSLR images, unmanned aerial vehicle images taken in mountainous area, close-range object images. Experimental results show that the proposed scheme can match abundant of tie points and the sigma0 is less than 1/3 pixels. It demonstrates that the feasibility of the developed algorithm is high and is suitable for most of the photogrammetric applications.

Original languageEnglish
Title of host publication32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Pages2336-2341
Number of pages6
Publication statusPublished - 2011 Dec 1
Event32nd Asian Conference on Remote Sensing 2011, ACRS 2011 - Tapei, Taiwan
Duration: 2011 Oct 32011 Oct 7

Publication series

Name32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Volume4

Other

Other32nd Asian Conference on Remote Sensing 2011, ACRS 2011
CountryTaiwan
CityTapei
Period11-10-0311-10-07

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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  • Cite this

    Jhan, J. P., Rau, J-Y., Lin, C. C., & Shao, Y. C. (2011). Automatic tie-point matching using SURF-based image matching scheme. In 32nd Asian Conference on Remote Sensing 2011, ACRS 2011 (pp. 2336-2341). (32nd Asian Conference on Remote Sensing 2011, ACRS 2011; Vol. 4).