scholarly journals Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1132
Author(s):  
Mathieu Ribes ◽  
Gaspard Russias ◽  
Denis Tregoat ◽  
Antoine Fournier
Keyword(s):  
Hyperspectral Imaging ◽  
Plant Species ◽  
Imaging Techniques ◽  
Low Cost ◽  
Plant Phenotyping ◽  
Teaching Tools ◽  
The Cost ◽  
Single Pixel ◽  
Reflectance Measurements ◽  
Imaging Setup

Hyperspectral imaging techniques have been expanding considerably in recent years. The cost of current solutions is decreasing, but these high-end technologies are not yet available for moderate to low-cost outdoor and indoor applications. We have used some of the latest compressive sensing methods with a single-pixel imaging setup. Projected patterns were generated on Fourier basis, which is well-known for its properties and reduction of acquisition and calculation times. A low-cost, moderate-flow prototype was developed and studied in the laboratory, which has made it possible to obtain metrologically validated reflectance measurements using a minimal computational workload. From these measurements, it was possible to discriminate plant species from the rest of a scene and to identify biologically contrasted areas within a leaf. This prototype gives access to easy-to-use phenotyping and teaching tools at very low-cost.

scholarly journals Terahertz Single-Pixel Imaging Improved by Using Silicon Wafer with SiO2 Passivation

2020 ◽  
Vol 10 (7) ◽  
pp. 2427
Author(s):  
Rongbin She ◽  
Wenquan Liu ◽  
Guanglu Wei ◽  
Yuanfu Lu ◽  
Guangyuan Li
Keyword(s):  
Compressed Sensing ◽  
Silicon Wafer ◽  
Low Cost ◽  
Thz Imaging ◽  
Modulation Factor ◽  
Passivation Process ◽  
Chemical Passivation ◽  
The Cost ◽  
Single Pixel ◽  
Method Show

We demonstrate terahertz single-pixel imaging is improved by using a photomodulator based on silicon passivated with SiO 2 . By exploring various SiO 2 thicknesses, we show that the modulation factor of the as-fabricated terahertz photomodulator can reach 0.9, three times that based on bare silicon. This improvement originates from chemical passivation, as well as anti-reflection. Single-pixel imaging experiments based on the compressed sensing method show that reconstructed images adopting the new photomodulator have better quality than the conventional terahertz modulator based on bare silicon. Since the passivation process is routine and low cost, we expect this work will reduce the cost of terahertz photomodulator and single-pixel THz imaging, and advance their applications.

scholarly journals Compressive Coded Rotating Mirror Camera for High-Speed Imaging

Photonics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 34
Author(s):  
Amir Matin ◽  
Xu Wang
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Frame Rate ◽  
High Temporal Resolution ◽  
Dynamic Scenes ◽  
High Speed Imaging ◽  
Continuous Frame ◽  
The Cost ◽  
Compressed Data ◽  
Single Pixel

We develop a novel compressive coded rotating mirror (CCRM) camera to capture events at high frame rates in passive mode with a compact instrument design at a fraction of the cost compared to other high-speed imaging cameras. Operation of the CCRM camera is based on amplitude optical encoding (grey scale) and a continuous frame sweep across a low-cost detector using a motorized rotating mirror system which can achieve single pixel shift between adjacent frames. Amplitude encoding and continuous frame overlapping enable the CCRM camera to achieve a high number of captured frames and high temporal resolution without making sacrifices in the spatial resolution. Two sets of dynamic scenes have been captured at up to a 120 Kfps frame rate in both monochrome and colored scales in the experimental demonstrations. The obtained heavily compressed data from the experiment are reconstructed using the optimization algorithm under the compressive sensing (CS) paradigm and the highest sequence depth of 1400 captured frames in a single exposure has been achieved with the highest compression ratio of 368 compared to other CS-based high-speed imaging technologies. Under similar conditions the CCRM camera is 700× faster than conventional rotating mirror based imaging devices and could reach a frame rate of up to 20 Gfps.

A Prototype for a Palm-sized Photoacoustic Sensing Unit

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Fei Gao ◽  
Xiaohua Feng ◽  
Xilin Miao ◽  
Yuanjin Zheng
Keyword(s):  
Imaging Techniques ◽  
Low Cost ◽  
Low Frequency ◽  
Pulse Signal ◽  
Research Progress ◽  
Fundamental Physics ◽  
Sensing Applications ◽  
Data Acquisition Card ◽  
Potential Applications ◽  
The Cost

AbstractPhotoacoustic sensing and imaging techniques have experienced tremendous research progress, ranging from fundamental physics and methodologies to various biomedical and clinical applications in recent years. However, the state-of-art photoacoustic systems still suffer from high cost and bulky size, which hinders their potential applications for low-cost and portable diagnostics. In this paper, we propose the design for a palm-size photoacoustic sensor prototype. The design’s lower cost and smaller size would allow it to be used for portable photoacoustic sensing applications like oxygen saturation and temperature. By converting the high-frequency photoacoustic pulse signal to low-frequency photoacoustic DC signal through a rectifier circuit, the proposed photoacoustic receiver could potentially reduce the cost and device size efficiently, compared with the conventional highspeed data acquisition card interfaced with computer solutions. Preliminary testing is demonstrated to show its feasibility for photoacoustic sensing applications.

Advance Protection for Three Phase Induction Motor using Microcontroller Atmega32

2018 ◽  
Vol 8 (1) ◽  
pp. 172
Author(s):  
Karan S Belsare ◽  
Gajanan D Patil
Keyword(s):  
Induction Motor ◽  
Low Cost ◽  
Short Circuit ◽  
Cost Factor ◽  
Protection Scheme ◽  
Three Phase ◽  
The Cost

A low cost and reliable protection scheme has been designed for a three phase induction motor against unbalance voltages, under voltage, over voltage, short circuit and overheating protection. Taking the cost factor into consideration the design has been proposed using microcontroller Atmega32, MOSFETs, relays, small CTs and PTs. However the sensitivity of the protection scheme has been not compromised. The design has been tested online in the laboratory for small motors and the same can be implemented for larger motors by replacing the i-v converters and relays of suitable ratings.

Janus – A New Approach to Air Combat Pilot Training

2019 ◽  
Vol 2019 (4) ◽  
pp. 7-22
Author(s):  
Georges Bridel ◽  
Zdobyslaw Goraj ◽  
Lukasz Kiszkowiak ◽  
Jean-Georges Brévot ◽  
Jean-Pierre Devaux ◽  
...  
Keyword(s):  
Low Cost ◽  
Cost Effective ◽  
High Energy ◽  
Training System ◽  
Embedded Sensors ◽  
Pilot Training ◽  
New Approach ◽  
Combat Aircraft ◽  
Air Combat ◽  
The Cost

Abstract Advanced jet training still relies on old concepts and solutions that are no longer efficient when considering the current and forthcoming changes in air combat. The cost of those old solutions to develop and maintain combat pilot skills are important, adding even more constraints to the training limitations. The requirement of having a trainer aircraft able to perform also light combat aircraft operational mission is adding unnecessary complexity and cost without any real operational advantages to air combat mission training. Thanks to emerging technologies, the JANUS project will study the feasibility of a brand-new concept of agile manoeuvrable training aircraft and an integrated training system, able to provide a live, virtual and constructive environment. The JANUS concept is based on a lightweight, low-cost, high energy aircraft associated to a ground based Integrated Training System providing simulated and emulated signals, simulated and real opponents, combined with real-time feedback on pilot’s physiological characteristics: traditionally embedded sensors are replaced with emulated signals, simulated opponents are proposed to the pilot, enabling out of sight engagement. JANUS is also providing new cost effective and more realistic solutions for “Red air aircraft” missions, organised in so-called “Aggressor Squadrons”.

scholarly journals The Performances of Hyperspectral Sensors for Proximal Sensing of Nitrogen Levels in Wheat

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4550
Author(s):  
Huajian Liu ◽  
Brooke Bruning ◽  
Trevor Garnett ◽  
Bettina Berger
Keyword(s):  
Hyperspectral Imaging ◽  
High Throughput ◽  
Management Practices ◽  
Leaf Tissue ◽  
Plant Phenotyping ◽  
Proximal Sensing ◽  
N Content ◽  
Hyperspectral Sensors ◽  
Wheat Leaves ◽  
Non Destructive

The accurate and high throughput quantification of nitrogen (N) content in wheat using non-destructive methods is an important step towards identifying wheat lines with high nitrogen use efficiency and informing agronomic management practices. Among various plant phenotyping methods, hyperspectral sensing has shown promise in providing accurate measurements in a fast and non-destructive manner. Past applications have utilised non-imaging instruments, such as spectrometers, while more recent approaches have expanded to hyperspectral cameras operating in different wavelength ranges and at various spectral resolutions. However, despite the success of previous hyperspectral applications, some important research questions regarding hyperspectral sensors with different wavelength centres and bandwidths remain unanswered, limiting wide application of this technology. This study evaluated the capability of hyperspectral imaging and non-imaging sensors to estimate N content in wheat leaves by comparing three hyperspectral cameras and a non-imaging spectrometer. This study answered the following questions: (1) How do hyperspectral sensors with different system setups perform when conducting proximal sensing of N in wheat leaves and what aspects have to be considered for optimal results? (2) What types of photonic detectors are most sensitive to N in wheat leaves? (3) How do the spectral resolutions of different instruments affect N measurement in wheat leaves? (4) What are the key-wavelengths with the highest correlation to N in wheat? Our study demonstrated that hyperspectral imaging systems with satisfactory system setups can be used to conduct proximal sensing of N content in wheat with sufficient accuracy. The proposed approach could reduce the need for chemical analysis of leaf tissue and lead to high-throughput estimation of N in wheat. The methodologies here could also be validated on other plants with different characteristics. The results can provide a reference for users wishing to measure N content at either plant- or leaf-scales using hyperspectral sensors.

scholarly journals A low-cost wireless endoscope camera: a preliminary report

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
J. M. Lazarus ◽  
M. Ncube
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Video Transmission ◽  
Low Cost ◽  
Battery Life ◽  
Resource Constrained ◽  
High Definition ◽  
Industry Standard ◽  
Constrained Environments ◽  
The Cost

Abstract Background Technology currently used for surgical endoscopy was developed and is manufactured in high-income economies. The cost of this equipment makes technology transfer to resource constrained environments difficult. We aimed to design an affordable wireless endoscope to aid visualisation during rigid endoscopy and minimally invasive surgery (MIS). The initial prototype aimed to replicate a 4-mm lens used in rigid cystoscopy. Methods Focus was placed on using open-source resources to develop the wireless endoscope to significantly lower the cost and make the device accessible for resource-constrained settings. An off the shelf miniature single-board computer module was used because of its low cost (US$10) and its ability to handle high-definition (720p) video. Open-source Linux software made monitor mode (“hotspot”) wireless video transmission possible. A 1280 × 720 pixel high-definition tube camera was used to generate the video signal. Video is transmitted to a standard laptop computer for display. Bench testing included latency of wireless digital video transmission. Comparison to industry standard wired cameras was made including weight and cost. The battery life was also assessed. Results In comparison with industry standard cystoscope lens, wired camera, video processing unit and light source, the prototype costs substantially less. (US$ 230 vs 28 000). The prototype is light weight (184 g), has no cables tethering and has acceptable battery life (of over 2 h, using a 1200 mAh battery). The camera transmits video wirelessly in near real time with only imperceptible latency of < 200 ms. Image quality is high definition at 30 frames per second. Colour rendering is good, and white balancing is possible. Limitations include the lack of a zoom. Conclusion The novel wireless endoscope camera described here offers equivalent high-definition video at a markedly reduced cost to contemporary industry wired units and could contribute to making minimally invasive surgery possible in resource-constrained environments.

scholarly journals Rapid Foreign Object Detection System on Seaweed Using VNIR Hyperspectral Imaging

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5279
Author(s):  
Dong-Hoon Kwak ◽  
Guk-Jin Son ◽  
Mi-Kyung Park ◽  
Young-Duk Kim
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Hyperspectral Imaging ◽  
High Speed ◽  
Detection System ◽  
Imaging Techniques ◽  
Foreign Object ◽  
Subtraction Method ◽  
Foreign Objects ◽  
Time Operation

The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed.

scholarly journals Supervised Machine Learning Methods and Hyperspectral Imaging Techniques Jointly Applied for Brain Cancer Classification

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3827
Author(s):  
Gemma Urbanos ◽  
Alberto Martín ◽  
Guillermo Vázquez ◽  
Marta Villanueva ◽  
Manuel Villa ◽  
...  
Keyword(s):  
Machine Learning ◽  
Blood Vessel ◽  
Hyperspectral Imaging ◽  
Imaging Techniques ◽  
Venous Blood ◽  
Healthy Tissue ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Arterial Blood

Hyperspectral imaging techniques (HSI) do not require contact with patients and are non-ionizing as well as non-invasive. As a consequence, they have been extensively applied in the medical field. HSI is being combined with machine learning (ML) processes to obtain models to assist in diagnosis. In particular, the combination of these techniques has proven to be a reliable aid in the differentiation of healthy and tumor tissue during brain tumor surgery. ML algorithms such as support vector machine (SVM), random forest (RF) and convolutional neural networks (CNN) are used to make predictions and provide in-vivo visualizations that may assist neurosurgeons in being more precise, hence reducing damages to healthy tissue. In this work, thirteen in-vivo hyperspectral images from twelve different patients with high-grade gliomas (grade III and IV) have been selected to train SVM, RF and CNN classifiers. Five different classes have been defined during the experiments: healthy tissue, tumor, venous blood vessel, arterial blood vessel and dura mater. Overall accuracy (OACC) results vary from 60% to 95% depending on the training conditions. Finally, as far as the contribution of each band to the OACC is concerned, the results obtained in this work are 3.81 times greater than those reported in the literature.

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