scholarly journals Active IR location as the roadway profilometry method

2021 ◽  
Vol 2140 (1) ◽  
pp. 012032
Author(s):  
V L Khmelev ◽  
A F Fominykh
Keyword(s):  
Depth Map ◽  
Minimum Size ◽  
Scanning System ◽  
Distance Measurements ◽  
Ir Radiation ◽  
Multiple Sample ◽  
Statistical Studies ◽  
Mechanical Scanning ◽  
Classical Computer ◽  
Surface Quality Control

Abstract This article observe a using of active infrared beam location as roadway surface quality control. Changes in the spatial structure of the emitted IR radiation by surfaces within the capture scene allow creating a depth map of this scene. An optical camera makes it possible to use classical computer vision methods for stitching a depth map. For testing the possibility of using this approach, we made statistical studies on a multiple sample of distance measurements. Here we explain two experimental schemes with a programmable mechanical scanning system. The first one, we had determined the distance, which the image is capture accurately. The second, we measure the planar resolution, a minimum size of the defect that recognize by the infrared beam location system.

A New Kinect-Based Scanning System and its Application

2015 ◽  
Vol 764-765 ◽  
pp. 1375-1379 ◽  
Author(s):  
Cheng Tiao Hsieh
Keyword(s):  
Point Cloud ◽  
Depth Map ◽  
Bilateral Filter ◽  
Point Clouds ◽  
Digital Fabrication ◽  
Surface Model ◽  
Scanning System ◽  
3D Registration ◽  
Noise Point

This paper aims at presenting a simple approach utilizing a Kinect-based scanner to create models available for 3D printing or other digital manufacturing machines. The outputs of Kinect-based scanners are a depth map and they usually need complicated computational processes to prepare them ready for a digital fabrication. The necessary processes include noise filtering, point cloud alignment and surface reconstruction. Each process may require several functions and algorithms to accomplish these specific tasks. For instance, the Iterative Closest Point (ICP) is frequently used in a 3D registration and the bilateral filter is often used in a noise point filtering process. This paper attempts to develop a simple Kinect-based scanner and its specific modeling approach without involving the above complicated processes.The developed scanner consists of an ASUS’s Xtion Pro and rotation table. A set of organized point cloud can be generated by the scanner. Those organized point clouds can be aligned precisely by a simple transformation matrix instead of the ICP. The surface quality of raw point clouds captured by Kinect are usually rough. For this drawback, this paper introduces a solution to obtain a smooth surface model. Inaddition, those processes have been efficiently developed by free open libraries, VTK, Point Cloud Library and OpenNI.

scholarly journals A High Reliability 3D Scanning Measurement of the Complex Shape Rail Surface of the Electromagnetic Launcher

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1485 ◽  
Author(s):  
Zhaoxin Wang ◽  
Baoming Li
Keyword(s):  
Signal To Noise Ratio ◽  
High Reliability ◽  
Depth Map ◽  
3D Scanning ◽  
Scanning System ◽  
Electromagnetic Launcher ◽  
Dim Light ◽  
Active Illumination ◽  
Binocular Stereovision ◽  
Acquisition Method

After an electromagnetic railgun launch, a series of damage phenomena may cause the inner bore surface to become complex, such as gouging and deposition. Furthermore, the rail surface will be uneven and blackened by oxidation. To understand these forms of rail degradation, many previous studies have mentioned several surface scanning methods, but none of these can be used in the complex inner bore. Therefore, we present a 3D scanning system based on binocular stereovision technology combined with the active illumination, which can be used to obtain the rail surface topography under a complex inner bore environment. The laser dot projection is applied as the active illumination. In contrast with other active illumination, laser dot projection has high reconstruction reliability. By combining laser dot projection with binocular stereovision, the object can be completely reconstructed. In addition, an image acquisition method which can improve image signal-to-noise ratio is proposed. The proof-of-principle experiment of the system is done under dim light conditions. Through the experiment, the 3D depth map of the rail surface is obtained and the gouge crater is scanned out. Meanwhile, system evaluation and measurement uncertainty analysis have also been carried out.

scholarly journals Sector Rasterization Method for Images on a Video Device With Mechanical Scanning

2020 ◽  
pp. 182-193
Author(s):  
Yelizaveta Meleshko ◽  
◽  
Dmytro Bakin ◽  
Keyword(s):  
Video Transmission ◽  
Central Zone ◽  
Computing System ◽  
Linear Interpolation ◽  
Scanning System ◽  
Image Reproduction ◽  
Raster Image ◽  
Software Product ◽  
Mechanical Scanning ◽  
Embedded Computing System

The goal of this work was to create a method for sectoral rasterization for images on video devices with mechanical scanning that can be used for advertising purposes. Preparing an image for display on a machine with a mechanical sector scan requires the creation of software for transferring a classic rectangular raster to a sector raster. When implementing software for an embedded computing system of mechanical image scanning for advertising purposes, the task was to reproduce a raster image using concentrically located circles, which are divided into sectors. The ambiguity of the transition from a square to a sectorial raster lies in the variable area of the sectors as they move away from the center of the image. According to this fact, there are several sectors for each of the pixels near the central zone of the image, and several pixels for one sector to the periphery of the image. There is not possible to increase the resolution of a sector image due to hardware limitations, so a new method of sector rasterization for an image on a mechanically scanned video device was developed. The developed method combines algorithms that make it possible to transform a raster image into a sectorial raster using linear interpolation depending on the distance of the sector from the center of the image. Attention was also paid to assessing the time of the next complete revolution when starting the mechanical scanning system, which made it possible to reduce the time for obtaining a stable image from the moment the device was turned on. So, as the result of the research, the method of sectorial image rasterization was developed, as well as the algorithms that allow converting a raster image into a sectorial image were developed. Вased on the developed algorithms, the software product for an embedded image reproduction system and the software product for real-time video transmission over Wi-Fi communication with the conversion of a rectangular raster into a sector raster were created. By combining algorithms for converting a square raster to a sector one, the quality of image reproduction on a mechanically scanned video device was improved.

Real Time B-Mode Mechanical Scanning System

1975 ◽  
Author(s):  
Reginald C. Eggleton ◽  
Kenneth W. Johnston
Keyword(s):  
Real Time ◽  
Scanning System ◽  
Mechanical Scanning

MICRO-BEAM SCANNING PIXE IN NIRS AND THE APPLICATION TESTS TO BIOLOGICAL SAMPLES

2000 ◽  
Vol 10 (01n02) ◽  
pp. 71-75 ◽  
Author(s):  
M. Yukawa ◽  
H. Imaseki ◽  
O. Yukawa
Keyword(s):  
Single Cell ◽  
Biological Samples ◽  
Ring Structure ◽  
Minimum Size ◽  
Scanning System ◽  
Elemental Distribution ◽  
Fish Scale ◽  
Elemental Mapping ◽  
Beam Scanning ◽  
Pixe Analysis

Micro-beam scanning system for PIXE analysis newly installed in National Institute of Radiological Sciences (NIRS) was introduced in this paper. Fine ring structure of a fish scale was observed using elemental mapping with proton micro-beam scanning. Pollen was analyzed as one example of single cell to demonstrate the elemental distribution. The minimum size of the proton beam is estimated as 0.4×0.65 μ m .

scholarly journals 3D Reconstruction Method of Rapeseed Plants in the Whole Growth Period Using RGB-D Camera

2021 ◽  
Author(s):  
Xiaowen Teng ◽  
Guangsheng Zhou ◽  
Yuxuan Wu ◽  
Chenglong Huang ◽  
Wanjing Dong ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Point Cloud ◽  
Near Infrared ◽  
Infrared Image ◽  
Depth Map ◽  
Point Clouds ◽  
Scanning System ◽  
Reconstruction Method ◽  
Hardware Cost ◽  
Scan Time

The 3D reconstruction method using RGB-D camera has a good balance in hardware cost, point cloud quality and automation. However, due to the limitation of inherent structure and imaging principle, the acquired point cloud has problems such as a lot of noise and difficult registration. This paper proposes a three-dimensional reconstruction method using Azure Kinect to solve these inherent problems. Shoot color map, depth map and near-infrared image of the target from six perspectives by Azure Kinect sensor. Multiply the 8-bit infrared image binarization with the general RGB-D image alignment result provided by Microsoft to remove ghost images and most of the background noise. In order to filter the floating point and outlier noise of the point cloud, a neighborhood maximum filtering method is proposed to filter out the abrupt points in the depth map. The floating points in the point cloud are removed before generating the point cloud, and then using the through filter filters out outlier noise. Aiming at the shortcomings of the classic ICP algorithm, an improved method is proposed. By continuously reducing the size of the down-sampling grid and the distance threshold between the corresponding points, the point clouds of each view are continuously registered three times, until get the complete color point cloud. A large number of experimental results on rape plants show that the point cloud accuracy obtained by this method is 0.739mm, a complete scan time is 338.4 seconds, and the color reduction is high. Compared with a laser scanner, the proposed method has considerable reconstruction accuracy and a significantly ahead of the reconstruction speed, but the hardware cost is much lower and it is easy to automate the scanning system. This research shows a low-cost, high-precision 3D reconstruction technology, which has the potential to be widely used for non-destructive measurement of crop phenotype.

scholarly journals Miniaturised Low-Cost Gamma Scanning Platform for Contamination Identification, Localisation and Characterisation: A New Instrument in the Decommissioning Toolkit

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2884
Author(s):  
Yannick Verbelen ◽  
Peter G. Martin ◽  
Kamran Ahmad ◽  
Suresh Kaluvan ◽  
Thomas B. Scott
Keyword(s):  
Radiation Intensity ◽  
Gamma Ray ◽  
Low Cost ◽  
Single Point ◽  
Small Diameter ◽  
Radioactive Material ◽  
Polar Coordinate System ◽  
Scanning System ◽  
Distance Measurements ◽  
New Instrument

Formerly clandestine, abandoned and legacy nuclear facilities, whether associated with civil or military applications, represent a significant decommissioning challenge owing to the lack of knowledge surrounding the existence, location and types of radioactive material(s) that may be present. Consequently, mobile and highly deployable systems that are able to identify, spatially locate and compositionally assay contamination ahead of remedial actions are of vital importance. Deployment imposes constraints to dimensions resulting from small diameter access ports or pipes. Herein, we describe a prototype low-cost, miniaturised and rapidly deployable ‘cell characterisation’ gamma-ray scanning system to allow for the examination of enclosed (internal) or outdoor (external) spaces for radioactive ‘hot-spots’. The readout from the miniaturised and lead-collimated gamma-ray spectrometer, that is progressively rastered through a stepped snake motion, is combined with distance measurements derived from a single-point laser range-finder to obtain an array of measurements in order to yield a 3-dimensional point-cloud, based on a polar coordinate system—scaled for radiation intensity. Existing as a smaller and more cost-effective platform than presently available, we are able to produce a millimetre-accurate 3D volumetric rendering of a space—whether internal or external, onto which fully spectroscopic radiation intensity data can be overlain to pinpoint the exact positions at which (even low abundance) gamma-emitting materials exist.

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