scholarly journals Precise Inspection of Geometric Parameters for Polyvinyl Chloride Pipe Section Based on Computer Vision

2021 ◽  
Vol 38 (6) ◽  
pp. 1647-1655
Author(s):  
Qilin Bi ◽  
Minling Lai ◽  
Huiling Tang ◽  
Yanyao Guo ◽  
Jinyuan Li ◽  
...  
Keyword(s):  
Computer Vision ◽  
Polyvinyl Chloride ◽  
Imaging System ◽  
Low Cost ◽  
Region Of Interest ◽  
Geometric Parameters ◽  
Outer Diameter ◽  
Pipe Section ◽  
Edge Operator ◽  
Pvc Pipe

The precise inspection of geometric parameters is crucial for quality control in the context of Industry 4.0. The current technique of precise inspection depends on the operation of professional personnel, and the measuring accuracy is restricted by the proficiency of operators. To solve the defects, this paper proposes a precise inspection framework for the geometric parameters of polyvinyl chloride (PVC) pipe section (G-PVC), using low-cost visual sensors and high-precision computer vision algorithms. Firstly, a robust imaging system was built to acquire images of a PVC pipe section under irregular illumination changes. Next, an engineering semantic model was established to calculate G-PVC like inner diameter, outer diameter, wall thickness, and roundness. After that, a region-of-interest (ROI) extraction algorithm was combined with an improved edge operator to obtain the coordinates of measured points on PVC end-face image in a stable and precise manner. Finally, our framework was proved highly precise and robust through experiments.

scholarly journals Seeing the Trees from the Forest: Using Modern Methods to Identify Individual Objects in a Cluttered Environment for Robots

2021 ◽  
Author(s):  
◽  
Josh Prow
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Low Cost ◽  
Region Of Interest ◽  
High Growth ◽  
Working Environment ◽  
Single Shot ◽  
Graphics Processors ◽  
High Definition ◽  
Depth Cameras

<p>Robotics and computer vision are areas of high growth across both industry and personal usage environments. Robots in industrial situations have been used to work in environments that are hazardous for humans or to perform basic tasks that require fine detail beyond that which human operators can reliably perform. These robotic solutions require a variety of sensors and cameras to navigate and identify objects within their working environment, as well as software and intelligent detection systems. These solutions generally require high definition depth cameras, laser range finders and computer vision algorithms, which are both expensive and require expensive graphics processors to run practically.  This thesis explores the option of a low-cost computer vision enabled robotic solution, which can operate within a forestry environment. Starting with the accuracy of camera technologies, testing two of the main cameras available for robotic vision, and demonstrating the benefits of the RealSense D435 by Intel over the Kinect for X-Box One. Followed by testing common object detection and recognition algorithms on different devices; considering the advantages and weaknesses of the determined models for the intended purpose of forestry.  These tests support other research on finding that the MobileNet Single Shot Detector has the fastest recognition speeds with accurate precision, however, it struggles where multiple objects were present, or the background was complex. In comparison, the Mask R-CNN had high accuracy and was able to identify objects consistently even with large numbers overlaid within a single frame.  A combined method based on the Faster R-CNN architecture with a MobileNet backbone and masking layers is proposed, developed and tested based on these findings. This method utilized the feature extraction and object detection abilities of the faster MobileNet in place of the traditionally ResNet based feature proposal networks, while still capitalizing on the benefits of the region of interest (ROI) align and masking from the Mask R-CNN architecture.  The results from this model did not meet the criteria required to recommend the model as an operational solution for the forestry environment. However, they do show that the model has higher performance and average precision than other models with similar frame rates on the non-CUDA enabled testing device. Demonstrating the technology and methodology has the potential to be the basis for a future solution to the problem of balancing accuracy and performance on a low performance or non GPU-enabled robotic unit.</p>

scholarly journals Seeing the Trees from the Forest: Using Modern Methods to Identify Individual Objects in a Cluttered Environment for Robots

2021 ◽  
Author(s):  
◽  
Josh Prow
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Low Cost ◽  
Region Of Interest ◽  
High Growth ◽  
Working Environment ◽  
Single Shot ◽  
Graphics Processors ◽  
High Definition ◽  
Depth Cameras

<p>Robotics and computer vision are areas of high growth across both industry and personal usage environments. Robots in industrial situations have been used to work in environments that are hazardous for humans or to perform basic tasks that require fine detail beyond that which human operators can reliably perform. These robotic solutions require a variety of sensors and cameras to navigate and identify objects within their working environment, as well as software and intelligent detection systems. These solutions generally require high definition depth cameras, laser range finders and computer vision algorithms, which are both expensive and require expensive graphics processors to run practically.  This thesis explores the option of a low-cost computer vision enabled robotic solution, which can operate within a forestry environment. Starting with the accuracy of camera technologies, testing two of the main cameras available for robotic vision, and demonstrating the benefits of the RealSense D435 by Intel over the Kinect for X-Box One. Followed by testing common object detection and recognition algorithms on different devices; considering the advantages and weaknesses of the determined models for the intended purpose of forestry.  These tests support other research on finding that the MobileNet Single Shot Detector has the fastest recognition speeds with accurate precision, however, it struggles where multiple objects were present, or the background was complex. In comparison, the Mask R-CNN had high accuracy and was able to identify objects consistently even with large numbers overlaid within a single frame.  A combined method based on the Faster R-CNN architecture with a MobileNet backbone and masking layers is proposed, developed and tested based on these findings. This method utilized the feature extraction and object detection abilities of the faster MobileNet in place of the traditionally ResNet based feature proposal networks, while still capitalizing on the benefits of the region of interest (ROI) align and masking from the Mask R-CNN architecture.  The results from this model did not meet the criteria required to recommend the model as an operational solution for the forestry environment. However, they do show that the model has higher performance and average precision than other models with similar frame rates on the non-CUDA enabled testing device. Demonstrating the technology and methodology has the potential to be the basis for a future solution to the problem of balancing accuracy and performance on a low performance or non GPU-enabled robotic unit.</p>

A technique for protecting delicate specimens during processing

1989 ◽  
Vol 47 ◽  
pp. 982-983
Author(s):  
R.J. Mount ◽  
R.V. Harrison
Keyword(s):  
Basilar Membrane ◽  
Low Cost ◽  
Organ Of Corti ◽  
Region Of Interest ◽  
Sensory Epithelium ◽  
Physical Damage ◽  
Air Drying ◽  
Specimen Handling ◽  
Two Component

The sensory end organ of the ear, the organ of Corti, rests on a thin basilar membrane which lies between the bone of the central modiolus and the bony wall of the cochlea. In vivo, the organ of Corti is protected by the bony wall which totally surrounds it. In order to examine the sensory epithelium by scanning electron microscopy it is necessary to dissect away the protective bone and expose the region of interest (Fig. 1). This leaves the fragile organ of Corti susceptible to physical damage during subsequent handling. In our laboratory cochlear specimens, after dissection, are routinely prepared by the O-T- O-T-O technique, critical point dried and then lightly sputter coated with gold. This processing involves considerable specimen handling including several hours on a rotator during which the organ of Corti is at risk of being physically damaged. The following procedure uses low cost, readily available materials to hold the specimen during processing ,preventing physical damage while allowing an unhindered exchange of fluids.Following fixation, the cochlea is dehydrated to 70% ethanol then dissected under ethanol to prevent air drying. The holder is prepared by punching a hole in the flexible snap cap of a Wheaton vial with a paper hole punch. A small amount of two component epoxy putty is well mixed then pushed through the hole in the cap. The putty on the inner cap is formed into a “cup” to hold the specimen (Fig. 2), the putty on the outside is smoothed into a “button” to give good attachment even when the cap is flexed during handling (Fig. 3). The cap is submerged in the 70% ethanol, the bone at the base of the cochlea is seated into the cup and the sides of the cup squeezed with forceps to grip it (Fig.4). Several types of epoxy putty have been tried, most are either soluble in ethanol to some degree or do not set in ethanol. The only putty we find successful is “DUROtm MASTERMENDtm Epoxy Extra Strength Ribbon” (Loctite Corp., Cleveland, Ohio), this is a blue and yellow ribbon which is kneaded to form a green putty, it is available at many hardware stores.

scholarly journals An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 343
Author(s):  
Kim Bjerge ◽  
Jakob Bonde Nielsen ◽  
Martin Videbæk Sepstrup ◽  
Flemming Helsing-Nielsen ◽  
Toke Thomas Høye
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Vision System ◽  
Low Cost ◽  
Light Trap ◽  
Automatic Monitoring ◽  
Light Sources ◽  
Monitoring Methods ◽  
Computer Vision System ◽  
Substantial Investment

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.

scholarly journals A Novel Electrically Small Ground-Penetrating Radar Patch Antenna with a Parasitic Ring for Respiration Detection

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1930
Author(s):  
Di Shi ◽  
Taimur Aftab ◽  
Gunnar Gidion ◽  
Fatma Sayed ◽  
Leonhard M. Reindl
Keyword(s):  
Ground Penetrating Radar ◽  
Patch Antenna ◽  
Low Cost ◽  
Substrate Material ◽  
Geometric Parameters ◽  
Gas Explosions ◽  
Aerial Vehicle ◽  
Electromagnetic Characteristics ◽  
Ground Penetrating ◽  
Quick Search

An electrically small patch antenna with a low-cost high-permittivity ceramic substrate material for use in a ground-penetrating radar is proposed in this work. The antenna is based on a commercial ceramic 915 MHz patch antenna with a size of 25 × 25 × 4 mm3 and a weight of 12.9 g. The influences of the main geometric parameters on the antenna’s electromagnetic characteristics were comprehensively studied. Three bandwidth improvement techniques were sequentially applied to optimize the antenna: tuning the key geometric parameters, adding cuts on the edges, and adding parasitic radiators. The designed antenna operates at around 1.3 GHz and has more than 40 MHz continuous −3 dB bandwidth. In comparison to the original antenna, the −3 and −6 dB fractional bandwidth is improved by 1.8 times and 4 times, respectively. Two antennas of the proposed design together with a customized radar were installed on an unmanned aerial vehicle (UAV) for a quick search for survivors after earthquakes or gas explosions without exposing the rescue staff to the uncertain dangers of moving on the debris.

Low-cost high-performance CMOS terahertz imaging system

2015 ◽  
Author(s):  
Chung Hsing Li ◽  
Tzu-Chao Yan ◽  
Yuhsin Chang ◽  
Chyong Chen ◽  
Chien-Nan Kuo
Keyword(s):  
High Performance ◽  
Imaging System ◽  
Low Cost ◽  
Terahertz Imaging

A low-cost laboratory thermal wave imaging system

1984 ◽  
Vol 17 (6) ◽  
pp. 526-532 ◽  
Author(s):  
G F Kirkbright ◽  
R M Miller ◽  
A Rzadkiewicz
Keyword(s):  
Thermal Wave ◽  
Imaging System ◽  
Low Cost ◽  
Wave Imaging ◽  
Thermal Wave Imaging

One Touch Workpiece Verification System for CNC Machining Using a Low-Cost Computer Vision Approach

2016 ◽  
Author(s):  
Maxwell K. Micali ◽  
Hayley M. Cashdollar ◽  
Zachary T. Gima ◽  
Mitchell T. Westwood
Keyword(s):  
Computer Vision ◽  
Low Cost ◽  
Cnc Machining ◽  
Potential Operator ◽  
Cnc Milling ◽  
Machining Processes ◽  
Loop Control ◽  
Operator Error ◽  
Verification System ◽  
Milling Machines

While CNC programmers have powerful tools to develop optimized toolpaths and machining plans, these efforts can be wholly undermined by something as simple as human operator error during fixturing. This project addresses that potential operator error with a computer vision approach to provide coarse, closed-loop control between fixturing and machining processes. Prior to starting the machining cycle, a sensor suite detects the geometry that is currently fixtured using computer vision algorithms and compare this geometry to a CAD reference. If the detected and reference geometries are not similar, the machining cycle will not start, and an alarm will be raised. The outcome of this project is the proof of concept of a low-cost, machine/controller agnostic solution that is applied to CNC milling machines. The Workpiece Verification System (WVS) prototype implemented in this work cost a total of $100 to build, and all of the processing is performed on the self-contained platform. This solution has additional applications beyond milling that the authors are exploring.

scholarly journals Fast, Robust, and Low-Cost Microwave Imaging of Multiple Non-Metallic Pipes

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1762
Author(s):  
Yuki Gao ◽  
Maryam Ravan ◽  
Reza K. Amineh
Keyword(s):  
Antenna Arrays ◽  
Oil And Gas ◽  
Imaging System ◽  
Imaging Techniques ◽  
Low Cost ◽  
Microwave Imaging ◽  
Airport Security ◽  
Destructive Testing ◽  
Security Screening ◽  
Industrial Sectors

The use of non-metallic pipes and composite components that are low-cost, durable, light-weight, and resilient to corrosion is growing rapidly in various industrial sectors such as oil and gas industries in the form of non-metallic composite pipes. While these components are still prone to damages, traditional non-destructive testing (NDT) techniques such as eddy current technique and magnetic flux leakage technique cannot be utilized for inspection of these components. Microwave imaging can fill this gap as a favorable technique to perform inspection of non-metallic pipes. Holographic microwave imaging techniques are fast and robust and have been successfully employed in applications such as airport security screening and underground imaging. Here, we extend the use of holographic microwave imaging to inspection of multiple concentric pipes. To increase the speed of data acquisition, we utilize antenna arrays along the azimuthal direction in a cylindrical setup. A parametric study and demonstration of the performance of the proposed imaging system will be provided.

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