Texture Mapping Method of Laser Point Cloud and Digital Image Based on Projection Transformation

2013 ◽  
Vol 864-867 ◽  
pp. 2792-2798
Author(s):  
Yun Cai ◽  
Hao Li ◽  
Ming Fei Wu ◽  
Biao Yang
Keyword(s):  
High Resolution ◽  
Digital Image ◽  
Point Cloud ◽  
Digital Images ◽  
Three Dimensional ◽  
Texture Mapping ◽  
Mapping Method ◽  
Spherical Image ◽  
Transformation Relation ◽  
Projection Transformation

In view of the lack of high-precision and high-resolution texture information of three-dimensional laser point cloud, this paper proposes a fusion method of three-dimensional laser point cloud and high-resolution digital images. Firstly the point cloud is transformed to the spherical image of laser intensity by projection. Then the rigorous projection transformation relation between the external digital image and three-dimensional point cloud is constructed easily through spherical image and feature information. Finally the color information of the point cloud is given by digital images. The experiment indicates that the novel method is able to avoid the layout difficulty of control points in the field and operating the three-dimensional data of indoor work, and meanwhile achieve the control of geometric accuracy.

scholarly journals High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5373 ◽  
Author(s):  
Jingxin Su ◽  
Ryuji Miyazaki ◽  
Toru Tamaki ◽  
Kazufumi Kaneda
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Cloud Model ◽  
Three Dimensional ◽  
Road Surface ◽  
Surface Elevation ◽  
Regular Grid ◽  
Real World Data ◽  
Mobile Mapping ◽  
Cloud Data

As mobile mapping systems become a mature technology, there are many applications for the process of the measured data. One interesting application is the use of driving simulators that can be used to analyze the data of tire vibration or vehicle simulations. In previous research, we presented our proposed method that can create a precise three-dimensional point cloud model of road surface regions and trajectory points. Our data sets were obtained by a vehicle-mounted mobile mapping system (MMS). The collected data were converted into point cloud data and color images. In this paper, we utilize the previous results as input data and present a solution that can generate an elevation grid for building an OpenCRG model. The OpenCRG project was originally developed to describe road surface elevation data, and also defined an open file format. As it can be difficult to generate a regular grid from point cloud directly, the road surface is first divided into straight lines, circular arcs, and and clothoids. Secondly, a non-regular grid which contains the elevation of road surface points is created for each road surface segment. Then, a regular grid is generated by accurately interpolating the elevation values from the non-regular grid. Finally, the curved regular grid (CRG) model files are created based on the above procedures, and can be visualized by OpenCRG tools. The experimental results on real-world data show that the proposed approach provided a very-high-resolution road surface elevation model.

Boundary Layer Detection Techniques Applied to Edge Detection

2019 ◽  
Vol 19 (02) ◽  
pp. 1950010 ◽  
Author(s):  
Fernando O. Guillén-Reyes ◽  
Francisco J. Domínguez-Mota
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Edge Detection ◽  
Digital Image ◽  
Execution Time ◽  
Digital Images ◽  
Intensity Function ◽  
Detection Techniques ◽  
Novel Algorithm

In this paper, we describe a novel algorithm for edge detection on a digital image, which is based locally on the directional averaged gradient properties of the intensity function, and produces very satisfactory results in high-resolution digital images in low execution time. Several examples show results which are comparable to those obtained by Canny and Sobel methods.

scholarly journals Digital image reduction for analysis of topological changes in the pore space of the rock matrix during chemical dissolution

2020 ◽  
pp. 319-328
Author(s):  
Д.И. Прохоров ◽  
Я.В. Базайкин ◽  
В.В. Лисица
Keyword(s):  
Digital Image ◽  
Linear Complexity ◽  
Digital Images ◽  
Pore Space ◽  
Three Dimensional ◽  
Chemical Dissolution ◽  
Rock Matrix ◽  
Persistence Diagrams ◽  
Topological Changes

В работе предложен алгоритм редукции трехмерных цифровых изображений для ускорения вычисления персистентных диаграмм, характеризующих изменения в топологии порового пространства образцов горной породы. Воксели для удаления выбираются исходя из структуры своей окрестности, что позволяет редуцировать изображение за линейное время. Показано, что эффективность алгоритма существенно зависит от сложности устройства порового пространства и размеров шагов фильтрации. A new algorithm for the reduction of three-dimensional digital images is proposed to improve the performance of persistence diagrams computing. These diagrams represent changes in topology of the pore space in the rock matrix. The algorithm has a linear complexity, since the removal of the voxel is based on the structure of its neighborhood. It is shown that the efficiency of the algorithm depends heavily on the complexity of the pore space and the size of filtering steps.

scholarly journals Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

Solid Earth ◽  
2017 ◽  
Vol 8 (6) ◽  
pp. 1241-1253 ◽  
Author(s):  
Samuel T. Thiele ◽  
Lachlan Grose ◽  
Anindita Samsu ◽  
Steven Micklethwaite ◽  
Stefan A. Vollgger ◽  
...  
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Multiple Scales ◽  
Three Dimensional ◽  
Point Clouds ◽  
Structural Features ◽  
Least Cost Path ◽  
Contact Mapping ◽  
The North ◽  
Contact Patterns

Abstract. The advent of large digital datasets from unmanned aerial vehicle (UAV) and satellite platforms now challenges our ability to extract information across multiple scales in a timely manner, often meaning that the full value of the data is not realised. Here we adapt a least-cost-path solver and specially tailored cost functions to rapidly interpolate structural features between manually defined control points in point cloud and raster datasets. We implement the method in the geographic information system QGIS and the point cloud and mesh processing software CloudCompare. Using these implementations, the method can be applied to a variety of three-dimensional (3-D) and two-dimensional (2-D) datasets, including high-resolution aerial imagery, digital outcrop models, digital elevation models (DEMs) and geophysical grids. We demonstrate the algorithm with four diverse applications in which we extract (1) joint and contact patterns in high-resolution orthophotographs, (2) fracture patterns in a dense 3-D point cloud, (3) earthquake surface ruptures of the Greendale Fault associated with the Mw7.1 Darfield earthquake (New Zealand) from high-resolution light detection and ranging (lidar) data, and (4) oceanic fracture zones from bathymetric data of the North Atlantic. The approach improves the consistency of the interpretation process while retaining expert guidance and achieves significant improvements (35–65 %) in digitisation time compared to traditional methods. Furthermore, it opens up new possibilities for data synthesis and can quantify the agreement between datasets and an interpretation.

scholarly journals Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

2017 ◽  
Author(s):  
Samuel T. Thiele ◽  
Lachlan Grose ◽  
Anindita Samsu ◽  
Steven Micklethwaite ◽  
Stefan A. Vollgger ◽  
...  
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Multiple Scales ◽  
Earth Science ◽  
Three Dimensional ◽  
Point Clouds ◽  
Structural Features ◽  
Least Cost Path ◽  
Contact Mapping ◽  
The North

Abstract. Two centuries ago William Smith produced the first geological map of England and Wales, an achievement that underlined the importance of mapping geological contacts and structures as perhaps the most fundamental skill set in earth science. The advent of large digital datasets from unmanned aerial vehicle (UAV) and satellite platforms now challenges our ability to extract information across multiple scales in a timely manner, often meaning that the full value of the data is not realised. Here we adapt a least-cost-path solver and specially tailored cost-functions to rapidly extract and measure structural features from point cloud and raster datasets. We implement the method in the geographic information system QGIS and the point cloud and mesh processing software CloudCompare. Using these implementations, the method can be applied to a variety of three-dimensional (3D) and two-dimensional (2D) datasets including high-resolution aerial imagery, virtual outcrop models, digital elevation models (DEMs) and geophysical grids. We demonstrate the algorithm with four diverse applications, where we extract: (1) joint and contact patterns in high-resolution orthophotographs; (2) fracture patterns in a dense 3D point cloud; (3) earthquake surface ruptures of the Greendale Fault associated with the Mw7.1 Darfield earthquake (New Zealand) from high-resolution light detection and ranging (LiDAR) data, and; (4) oceanic fracture zones from bathymetric data of the North Atlantic. The approach improves the objectivity and consistency of the interpretation process while retaining expert-guidance, and achieves significant improvements (35–65 %) in digitisation time compared to traditional methods. Furthermore, it opens up new possibilities for data synthesis and can quantify the agreement between datasets and an interpretation.

scholarly journals TOWARDS GLOBALLY CONSISTENT SCAN MATCHINGWITH GROUND TRUTH INTEGRATION

2015 ◽  
Vol XL-3/W2 ◽  
pp. 59-64
Author(s):  
J. Gailis ◽  
A. Nüchter
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Simultaneous Localization And Mapping ◽  
Ground Truth ◽  
Mapping Method ◽  
Coordinate Frame ◽  
Scan Matching ◽  
Localization And Mapping ◽  
Real World Datasets ◽  
Ground Truth Information

The scan matching based simultaneous localization and mapping method with six dimensional poses is capable of creating a three dimensional point cloud map of the environment, as well as estimating the six dimensional path that the vehicle has travelled. The essence of it is the registering and matching of sequentially acquired 3D laser scans, while moving along a path, in a common coordinate frame in order to provide 6D pose estimations at the respective positions, as well as create a three dimensional map of the environment. An approach that could drastically improve the reliability of acquired data is to integrate available ground truth information. This paper is about implementing such functionality as a contribution to 6D SLAM (simultaneous localization and mapping with 6 DoF) in the 3DTK – The 3D Toolkit software (Nüchter and Lingemann, 2011), as well as test the functionality of the implementation using real world datasets.

scholarly journals A Novel Hybrid Secure Image Encryption Based on Julia Set of Fractals and 3D Lorenz Chaotic Map

Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 274 ◽  
Author(s):  
Fawad Masood ◽  
Jawad Ahmad ◽  
Syed Aziz Shah ◽  
Sajjad Shaukat Jamal ◽  
Iqtadar Hussain
Keyword(s):  
Digital Image ◽  
Chaotic Maps ◽  
Digital Images ◽  
Julia Set ◽  
Chaotic Map ◽  
Three Dimensional ◽  
Image Security ◽  
Average Value ◽  
Encryption Schemes ◽  
Security Test

Chaos-based encryption schemes have attracted many researchers around the world in the digital image security domain. Digital images can be secured using existing chaotic maps, multiple chaotic maps, and several other hybrid dynamic systems that enhance the non-linearity of digital images. The combined property of confusion and diffusion was introduced by Claude Shannon which can be employed for digital image security. In this paper, we proposed a novel system that is computationally less expensive and provided a higher level of security. The system is based on a shuffling process with fractals key along with three-dimensional Lorenz chaotic map. The shuffling process added the confusion property and the pixels of the standard image is shuffled. Three-dimensional Lorenz chaotic map is used for a diffusion process which distorted all pixels of the image. In the statistical security test, means square error (MSE) evaluated error value was greater than the average value of 10000 for all standard images. The value of peak signal to noise (PSNR) was 7.69(dB) for the test image. Moreover, the calculated correlation coefficient values for each direction of the encrypted images was less than zero with a number of pixel change rate (NPCR) higher than 99%. During the security test, the entropy values were more than 7.9 for each grey channel which is almost equal to the ideal value of 8 for an 8-bit system. Numerous security tests and low computational complexity tests validate the security, robustness, and real-time implementation of the presented scheme.

scholarly journals 3D Reconstruction of Irregular Buildings and Buddha Statues

2014 ◽  
Vol II-4 ◽  
pp. 91-94
Author(s):  
K. Zhang ◽  
M.-j. Li
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Main Idea ◽  
Texture Mapping ◽  
3D Laser Scanning ◽  
Surface Data ◽  
Irregular Buildings ◽  
3D Scene ◽  
Modelling Methods

Three-dimensional laser scanning could acquire object’s surface data quickly and accurately. However, the post-processing of point cloud is not perfect and could be improved. Based on the study of 3D laser scanning technology, this paper describes the details of solutions to modelling irregular ancient buildings and Buddha statues in Jinshan Temple, which aiming at data acquisition, modelling and texture mapping, etc. In order to modelling irregular ancient buildings effectively, the structure of each building is extracted manually by point cloud and the textures are mapped by the software of 3ds Max. The methods clearly combine 3D laser scanning technology with traditional modelling methods, and greatly improves the efficiency and accuracy of the ancient buildings restored. On the other hand, the main idea of modelling statues is regarded as modelling objects in reverse engineering. The digital model of statues obtained is not just vivid, but also accurate in the field of surveying and mapping. On this basis, a 3D scene of Jinshan Temple is reconstructed, which proves the validity of the solutions.

scholarly journals Analysis of Wave-Induced Current Using Digital Image Correlation Techniques

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Bumshick Shin ◽  
KyuHan Kim
Keyword(s):  
High Resolution ◽  
Digital Image Correlation ◽  
Digital Image ◽  
Three Dimensional ◽  
Image Data ◽  
Video Camera ◽  
Image Correlation ◽  
Correlation Technique ◽  
Induced Current ◽  
Wave Induced

Recently, advancement of digital image techniques and communications technology has enabled the application of existing images for scientific purposes. Furthermore, both quantitative and qualitative analyses of images have become possible through image processing such as transmit/storage of digital image data and image rectification. In this study, a coast having representative characteristics of east coast of Korea was selected with having erosion in winter, and the sedimentation in summer takes place repeatedly. Three-dimensional hydraulic model test was conducted to analyze its outcomes by a digital image correlation technique in order to understand the wave-induced current affecting the sediment transport. For this study, images filmed by the high-sensitive and high-resolution video camera were converted into stopped images of regular intervals and then those converted images were used for the following procedure to analyze flow and velocity into digital coordinates. The outcomes from interpretation of images filmed by the high-sensitive and high-resolution video camera can be utilized as a very useful analysis method for appreciating the generation mechanism and movement route of longshore current and rip current.

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