Low-Cost Laser Scanning System Design

Akyol, Onur; Duran, Zaide

doi:10.1007/s10946-014-9419-2

Cited by 15 publications

(4 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Laser scanning technology is a system that enables the representation of object surfaces with 3D coordinates. Essentially, the distance between the scanner and a specific point on the object's surface is determined with high accuracy by measuring the round-trip time of the laser signal [26]. According to the summarized fieldwork presented in the diagram on the left side in Figure 5, session locations and scanning parameters are crucial.…”

Section: D Point Cloud Imagementioning

confidence: 99%

Restitution Proposal for Medicine Pools in the Ancient City of Heraion Teichos Using Point Cloud Data

Cigdem Zagra Oz,

Atik

2024

Point Cloud Generation and Its Applications [Working Title]

View full text Add to dashboard Cite

Heraion Teichos is a Thracian city in northwestern Turkey. By using modern technologies in this ancient city, the benefits that modern technologies can provide to archeological excavations have been investigated. The main purpose of this research is to understand how modern technologies can be used to increase accuracy and precision by examining the opportunities offered by developing technology in archeological studies. How these technologies were effectively integrated into the archeological field was examined, focusing on excavation methods, digital documentation, and architectural remains of the ancient city, especially three ancient medicine production pools. This research aimed to obtain strong results by integrating traditional excavation methods with modern technology. The Heraion Teichos example demonstrates how modern technologies can be used effectively in archeological research and constitutes an example that can guide similar studies in the future.

show abstract

Section: D Point Cloud Imagementioning

confidence: 99%

Restitution Proposal for Medicine Pools in the Ancient City of Heraion Teichos Using Point Cloud Data

Cigdem Zagra Oz,

Atik

2024

Point Cloud Generation and Its Applications [Working Title]

View full text Add to dashboard Cite

show abstract

“…Due of their widespread use and comprehensive 3D description, point clouds are popular data sources. The main interest of photogrammetry is the 3D reconstruction of objects from images [2]. Recently, dense point clouds of large areas can be produced using algorithms such as Structure From Motion (SfM) [3].…”

Section: Introductionmentioning

confidence: 99%

Explainable Artificial Intelligence for Machine Learning-Based Photogrammetric Point Cloud Classification

Atik,

Duran,

Seker

2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Self Cite

View full text Add to dashboard Cite

Point clouds are one of the widely used data sources for spatial modeling. Artificial intelligence approaches have become an important tool for understanding and extracting semantic information of point clouds. In particular, the explainability of machine learning approaches for 3D data has not been sufficiently investigated. Moreover, existing studies are generally limited to object classification issues. This is a pioneer study that addresses the classification of photogrammetric point clouds in terms of explainable artificial intelligence. In this study, the explainability of black-box machine learning models in the context of the classification of photogrammetric point clouds was investigated. Each point in the point cloud is defined using geometric and spectral features. Additionally, the effect of selecting the most important of these features on the classification performance of ML models such as Random Forest, XGBoost and LightGBM was examined. The explainability of ML models was analyzed with Shapley Additive exPlanation (SHAP), an explainable artificial intelligence approach. SHAP analysis was compared with filterbased Information Gain (IG) and ReliefF methods for feature selection. Using the features selected with SHAP analysis, overall accuracy (OA) of 85.50% in the Ankeny dataset, 91.70% in the Building dataset and 83.28% in the Cadastre dataset was achieved with LightGBM. The evaluation with XGBoost shows overall accuracy of 85.22% for Ankeny, 91.21% for Building and 82.47% for Cadastre. The evaluation with RF shows overall accuracy of 83.70% for Ankeny, 89.08% for Building and 79.36% for Cadastre.

show abstract

“…It can make the conversion from object to data come true. And 3D entities can be duplicated with the help of 3D printer, which helps to motivate our imagination and creativity, and also enriches our life [5,6].…”

Section: Introductionmentioning

confidence: 99%

Research on laser stripe characteristics and center extraction algorithm for desktop laser scanner

et al. 2021

View full text Add to dashboard Cite

This study presents laser stripe center extraction algorithm for desktop-level 3D laser scanners. The laser stripe center extraction accuracy is an important factor affecting 3D scanning result. Desktop-level devices should have adaptability of a wide range of scanning objects. In this paper, laser stripe energy distribution characteristics with different laser stripe width, ambient light, materials and colors are obtained by experiments. Experiment results show that waveforms of bright spot, low brightness stripe and stripe with large width are complex or easily disturbed, so the center extraction algorithm of them are studied. The extraction effects of extremum method, gradient method and gray centroid method under different conditions are compared. Based on traditional grayscale value, a weighted grayscale value is proposed to extract laser stripe center. Standard deviations of extracted pixel position and fitting pixel position are calculated by different method with different weighted grayscale value. For different conditions, especially for different ambient light intensity, weight matrix plays an important role to extraction result.

show abstract

Low-Cost Laser Scanning System Design

Cited by 15 publications

References 2 publications

Restitution Proposal for Medicine Pools in the Ancient City of Heraion Teichos Using Point Cloud Data

Restitution Proposal for Medicine Pools in the Ancient City of Heraion Teichos Using Point Cloud Data

Explainable Artificial Intelligence for Machine Learning-Based Photogrammetric Point Cloud Classification

Research on laser stripe characteristics and center extraction algorithm for desktop laser scanner

Contact Info

Product

Resources

About