Accuracy Assessment of 3D Model Based on Laser Scan and Photogrammetry Data

Introduction

Authors

  • Marwa Mohamed Surveying, Engineering, Baghdad , Baghdad, Iraq
  • Zahraa Ezzulddin Hussein Surveying, Engineering, Baghdad , Baghdad, Iraq
  • Layla Kais Abbas Surveying, Engineering, Baghdad , Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2021.62.11.37

Keywords:

3D model, laser scanner, Agi photoscan, cloud compare, image processing, point cloud

Abstract

    A three-dimensional (3D) model extraction represents the best way to reflect the reality in all details. This explains the trends and tendency of many scientific disciplines towards making measurements, calculations and monitoring in various fields using such model. Although there are many ways to produce the 3D model like as images, integration techniques, and laser scanning, however, the quality of their products is not the same in terms of accuracy and detail. This article aims to assess the 3D point clouds model accuracy results from close range images and laser scan data based on Agi soft photoscan and cloud compare software to determine the compatibility of both datasets for several applications. College of Science, Departments of Mathematics and Computer in the University of Baghdad campus were exploited to create the proposed 3D model as this area location, which is one of the distinctive features of the university, allows making measurements freely from all sides. Results of this study supported by statistical analysis including 2 sample T-test and RMSE calculation in addition to visual comparison. Through this research, we note that the laser3D model provides many points in a short time, so it will reduce the field work and also its data is faster in processing to produce a reliable model of the scanned area compared with data derived from photogrammetry, then the difference were computed for all the reference points.

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Published

2022-01-03

Issue

Section

Remote Sensing

How to Cite

Accuracy Assessment of 3D Model Based on Laser Scan and Photogrammetry Data: Introduction. (2022). Iraqi Journal of Science, 62(11), 4195-4207. https://doi.org/10.24996/ijs.2021.62.11.37

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