scholarly journals Spatial Compare Filter Based Real-Time dead Pixel Correction Method for Infrared Camera

2016 ◽  
Vol 21 (12) ◽  
pp. 35-41
Author(s):  
Kil-Soo Moon
Keyword(s):  
Real Time ◽  
Infrared Camera ◽  
Correction Method

Real time injecting device with automated robust vein detection using near infrared camera and live video

2017 ◽  
Author(s):  
Tamim Ahmed ◽  
Khandker Sadia Rahman ◽  
Sk Subrina Shawlin ◽  
Mohammad Hasan ◽  
Arnab Bhattacharjee ◽  
...  
Keyword(s):  
Real Time ◽  
Near Infrared ◽  
Infrared Camera ◽  
Live Video

On Improving the Performances of Hydraulic Incremental Positioning Units with Mechanical Position Feedback

2012 ◽  
Vol 463-464 ◽  
pp. 1277-1280 ◽  
Author(s):  
Constantin Bucşan ◽  
Mihai Avram
Keyword(s):  
Real Time ◽  
Correction Method ◽  
Practical Application ◽  
Positioning Accuracy ◽  
Positioning Systems ◽  
Sensing System ◽  
Position Feedback ◽  
Time Determination ◽  
Interesting Solution

This paper presents a method for increasing the speed and the positioning accuracy of the positioning systems with mechanical position feedback. The method consists in using a position transducer for real time determination of the position of the load and correcting this position using an adequate algorithm. It is preferable not to modify the construction of the positioning unit, allowing the user to decide when to use this correction method according to the practical application. An interesting solution to this problem is to use an external space-position finding sensing system, as presented in the paper.

scholarly journals A study on the development of a light scattering particulate matter sensor and monitoring system

2020 ◽  
Vol 17 (3) ◽  
pp. 867-890
Author(s):  
Jun-Hee Choi ◽  
Hyun-Sug Cho
Keyword(s):  
Big Data ◽  
Particulate Matter ◽  
Light Scattering ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Gravimetric Method ◽  
Correction Method ◽  
Measurement Methods ◽  
Linear Correction

The gravimetric method, which is mainly used among particulate matter (PM) measurement methods, includes the disadvantages that it cannot measure PM in real time and it requires expensive equipment. To overcome these disadvantages, we have developed a light scattering type PM sensor that can be manufactured at low cost and can measure PM in real time. We have built a big data system that can systematically store and analyze the data collected through the developed sensor, as well as an environment where PM states can be monitored mobile in real time using such data. In addition, additional studies were conducted to analyze and correct the collected big data to overcome the problem of low accuracy, which is a disadvantage of the light scattering type PM sensor. We used a linear correction method and proceeded to adopt the most suitable value based on error and accuracy.

scholarly journals Real-Time Color Correction Method for a Low-Cost Still/Video Camera

2009 ◽  
Vol E92-D (1) ◽  
pp. 97-101
Author(s):  
Dongil HAN ◽  
Hak-Sung LEE ◽  
Chan IM ◽  
Seong Joon YOO
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Video Camera ◽  
Correction Method ◽  
Color Correction

A real-time fisheye video correction method based on Android smart-phone GPU

Optik ◽  
2020 ◽  
Vol 220 ◽  
pp. 165108
Author(s):  
Zhiyong Peng ◽  
Xiaopu Zhu ◽  
Jun Wu ◽  
Zujun Qin
Keyword(s):  
Real Time ◽  
Smart Phone ◽  
Correction Method

scholarly journals Use of SMAP Soil Moisture and Fitting Methods in Improving GPM Estimation in Near Real Time

2019 ◽  
Vol 11 (3) ◽  
pp. 368 ◽  
Author(s):  
Zhi Zhang ◽  
Dagang Wang ◽  
Guiling Wang ◽  
Jianxiu Qiu ◽  
Weilin Liao
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Mainland China ◽  
Correction Method ◽  
Cumulative Distribution ◽  
Area Index ◽  
Soil Moisture Data ◽  
Precipitation Product ◽  
Antecedent Precipitation ◽  
Potential Factors

Satellite-based precipitation products have been widely used in a variety of fields. However, near real time products still contain substantial biases compared with the ground data. Recent studies showed that surface soil moisture can be utilized in improving rainfall estimation as it reflects recent precipitation. In this study, soil moisture data from Soil Moisture Active Passive (SMAP) satellite and observation-based fitting are used to correct near real time satellite-based precipitation product Global Precipitation Measurement (GPM) in mainland China. The particle filter is adopted to assimilate the SMAP soil moisture into a simple hydrological model, the antecedent precipitation index (API) model; three fitting methods—i.e., linear, nonlinear, and cumulative distribution function (CDF) fitting corrections—both separately and in combination with the SMAP soil moisture data, are then used to correct GPM. The results show that the soil moisture-based correction significantly reduces the root mean square error (RMSE) and mean absolute errors (BIAS) of the original GPM product in most areas of China. The median RMSE value for daily precipitation over China is decreased by approximately 18% from 5.25 mm/day for the GPM estimates to 4.32 mm/day for the soil moisture corrected estimates, and the median BIAS value is decreased by approximately 13% from 2.03 mm/day to 1.76 mm/day. The fitting correction method alone also improves GPM, although to a lesser extent. The best performance is found when the SMAP soil moisture assimilation is combined with the linear fitting of observed precipitation, with a median RMSE of 4.00 mm/day and a BIAS of 1.69 mm/day. Despite significant reductions to the biases of the satellite precipitation product, none of these methods is effective in improving the correlation between the satellite product and observational reference. Leaf area index and the frequency of the SMAP overpasses are among the potential factors influencing the correction effect. This study highlights that combining soil moisture and historical precipitation information can effectively improve satellite-based precipitation products in near real time.

scholarly journals A Novel Tilt Correction Technique for Irradiance Sensors and Spectrometers On-Board Unmanned Aerial Vehicles

2018 ◽  
Vol 10 (12) ◽  
pp. 2068 ◽  
Author(s):  
Juha Suomalainen ◽  
Teemu Hakala ◽  
Raquel Alves de Oliveira ◽  
Lauri Markelin ◽  
Niko Viljanen ◽  
...  
Keyword(s):  
Real Time ◽  
Remote Sensing Data ◽  
Correction Method ◽  
Aerial Images ◽  
Aerial Image ◽  
Optical Remote Sensing ◽  
Processing Unit ◽  
Atmospheric Conditions ◽  
Tilt Correction ◽  
Correction Technique

In unstable atmospheric conditions, using on-board irradiance sensors is one of the only robust methods to convert unmanned aerial vehicle (UAV)-based optical remote sensing data to reflectance factors. Normally, such sensors experience significant errors due to tilting of the UAV, if not installed on a stabilizing gimbal. Unfortunately, such gimbals of sufficient accuracy are heavy, cumbersome, and cannot be installed on all UAV platforms. In this paper, we present the FGI Aerial Image Reference System (FGI AIRS) developed at the Finnish Geospatial Research Institute (FGI) and a novel method for optical and mathematical tilt correction of the irradiance measurements. The FGI AIRS is a sensor unit for UAVs that provides the irradiance spectrum, Real Time Kinematic (RTK)/Post Processed Kinematic (PPK) GNSS position, and orientation for the attached cameras. The FGI AIRS processes the reference data in real time for each acquired image and can send it to an on-board or on-cloud processing unit. The novel correction method is based on three RGB photodiodes that are tilted 10° in opposite directions. These photodiodes sample the irradiance readings at different sensor tilts, from which reading of a virtual horizontal irradiance sensor is calculated. The FGI AIRS was tested, and the method was shown to allow on-board measurement of irradiance at an accuracy better than ±0.8% at UAV tilts up to 10° and ±1.2% at tilts up to 15°. In addition, the accuracy of FGI AIRS to produce reflectance-factor-calibrated aerial images was compared against the traditional methods. In the unstable weather conditions of the experiment, both the FGI AIRS and the on-ground spectrometer were able to produce radiometrically accurate and visually pleasing orthomosaics, while the reflectance reference panels and the on-board irradiance sensor without stabilization or tilt correction both failed to do so. The authors recommend the implementation of the proposed tilt correction method in all future UAV irradiance sensors if they are not to be installed on a gimbal.

Image Capturing and Segmentation Method for Characters Marked on Hot Billets

2014 ◽  
Vol 945-949 ◽  
pp. 1830-1836 ◽  
Author(s):  
Qi Jie Zhao ◽  
Peng Cao ◽  
Qing Xu Meng
Keyword(s):  
Real Time ◽  
Correction Method ◽  
Segmentation Method ◽  
Color Information ◽  
Skew Correction ◽  
Production Environments ◽  
Real Time Image ◽  
Image Capturing ◽  
Acquisition Device ◽  
Time Image

Real-time detecting information marked on billets is important for automatically manufacturing and management in steelworks. But due to the tough production environments in steel enterprises, capturing and identifying characters marked on hot billets have many challenges. This paper presents a real-time image capturing and segmenting method with machine vision for characters marked on hot billets, and characters area is located based on color information of images. Furthermore, considering the marked characters are often slant, we proposed a kind of characters skew correction method to adjust the alignment of characters, and then segment characters into singles for recognition. Finally, with the proposed method, we have conducted some experiments in Baosteel Company. The result shows that our method can achieve 97% segmentation rate if we select proper image acquisition device and preprocessing algorithm. Additionally, it provides a new way for steel enterprise real-time capturing and segmenting marked characters image.

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