The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-4/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W4, 31–36, 2017
https://doi.org/10.5194/isprs-archives-XLII-4-W4-31-2017
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W4, 31–36, 2017
https://doi.org/10.5194/isprs-archives-XLII-4-W4-31-2017

  26 Sep 2017

26 Sep 2017

OPTIMIZATION OF CLOSE RANGE PHOTOGRAMMETRY NETWORK DESIGN APPLYING FUZZY COMPUTATION

A. S. Aminia A. S. Aminia
  • Dept. of Geomatic Engineering, Islamic Azad University – South Tehran Branch, Piroozi Street, Abuzar Boulevard, Dehhaghi Avenue, P. O. Box: 1777613651, Tehran, Iran

Keywords: Close range photogrammetry, Fuzzy computation, Network Design

Abstract. Measuring object 3D coordinates with optimum accuracy is one of the most important issues in close range photogrammetry. In this context, network design plays an important role in determination of optimum position of imaging stations. This is, however, not a trivial task due to various geometric and radiometric constraints affecting the quality of the measurement network. As a result, most camera stations in the network are defined on a try and error basis based on the user's experience and generic network concept. In this paper, we propose a post-processing task to investigate the quality of camera positions right after image capturing to achieve the best result. To do this, a new fuzzy reasoning approach is adopted, in which the constraints affecting the network design are all modeled. As a result, the position of all camera locations is defined based on fuzzy rules and inappropriate stations are determined. The experiments carried out show that after determination and elimination of the inappropriate images using the proposed fuzzy reasoning system, the accuracy of measurements is improved and enhanced about 17% for the latter network.