Integrated real-time polarization image sensor based on UV-NIL and calibration method

2022 ◽  
pp. 1-1
Author(s):  
Chuanlong Guan ◽  
Ran Zhang ◽  
Jinkui Chu ◽  
Ze Liu ◽  
Yuanyi Fan ◽  
...  
Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1713
Author(s):  
Hui Wang ◽  
Haofeng Hu ◽  
Xiaobo Li ◽  
Zijian Guan ◽  
Wanshan Zhu ◽  
...  

A demand for division of focal plane (DoFP) polarization image sensors grows rapidly as nanofabrication technologies become mature. The DoFP sensor can output real time data of polarization information. In this paper, a novel visualization method for angle of polarization (AoP) is proposed for DoFP polarization image sensors. The data characteristics of AoP are analyzed, and strategies for a visualization method are proposed which conforms to the characteristics of AoP data. According to these strategies, we propose a visualization method for AoP data based on three dimensional HSI color space. This method uses intensity and saturation to characterize the magnitude of the angle between the polarization direction and the horizontal direction wherein the hue indicates the deflection direction. It is shown by the numerical simulation that the noise in the AoP image can be suppressed by our visualization method. In addition, the real-world experiment results are consistent with the numerical simulation and verify that the AoP image obtained by our method can suppress the influence of characterization noise, and the image is simple and intuitive, which is advantageous to human vision. The proposed method can be directly used for the commercialized DoFP polarization image sensor to display real-time AoP data.


Author(s):  
Zachary Baum

Purpose: Augmented reality overlay systems can be used to project a CT image directly onto a patient during procedures. They have been actively trialed for computer-guided procedures, however they have not become commonplace in practice due to restrictions of previous systems. Previous systems have not been handheld, and have had complicated calibration procedures. We put forward a handheld tablet-based system for assisting with needle interventions. Methods: The system consists of a tablet display and a 3-D printed reusable and customizable frame. A simple and accurate calibration method was designed to align the patient to the projected image. The entire system is tracked via camera, with respect to the patient, and the projected image is updated in real time as the system is moved around the region of interest. Results: The resulting system allowed for 0.99mm mean position error in the plane of the image, and a mean position error of 0.61mm out of the plane of the image. This accuracy was thought to be clinically acceptable for tool using computer-guidance in several procedures that involve musculoskeletal needle placements. Conclusion: Our calibration method was developed and tested using the designed handheld system. Our results illustrate the potential for the use of augmented reality handheld systems in computer-guided needle procedures. 


2010 ◽  
Author(s):  
Pierre Tremblay ◽  
Louis Belhumeur ◽  
Martin Chamberland ◽  
André Villemaire ◽  
Patrick Dubois ◽  
...  

2014 ◽  
Vol 102 (10) ◽  
pp. 1435-1449 ◽  
Author(s):  
Milin Zhang ◽  
Xiaotie Wu ◽  
Nan Cui ◽  
Nader Engheta ◽  
Jan Van der Spiegel

2018 ◽  
Vol 81 (2) ◽  
pp. 839-851 ◽  
Author(s):  
Shuyu Tang ◽  
Eugene Milshteyn ◽  
Galen Reed ◽  
Jeremy Gordon ◽  
Robert Bok ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Helio Koiti Kuga ◽  
Valdemir Carrara

Attitude control of artificial satellites is dependent on information provided by its attitude determination process. This paper presents the implementation and tests of a fully self-contained algorithm for the attitude determination using magnetometers and accelerometers, for application on a satellite simulator based on frictionless air bearing tables. However, it is known that magnetometers and accelerometers need to be calibrated so as to allow that measurements are used to their ultimate accuracy. A calibration method is implemented which proves to be essential for improving attitude determination accuracy. For the stepwise real-time attitude determination, it was used the well-known QUEST algorithm which yields quick response with reduced computer resources. The algorithms are tested and qualified with actual data collected on the streets under controlled situations. For such street runaways, the experiment employs a solid-state magnetoresistive magnetometer and an IMU navigation block consisting of triads of accelerometers and gyros, with MEMS technology. A GPS receiver is used to record positional information. The collected measurements are processed through the developed algorithms, and comparisons are made for attitude determination using calibrated and noncalibrated data. The results show that the attitude accuracy reaches the requirements for real-time operation for satellite simulator platforms.


Sensors ◽  
2017 ◽  
Vol 17 (7) ◽  
pp. 1540 ◽  
Author(s):  
Binh Cao ◽  
Phuong Hoang ◽  
Sanghoon Ahn ◽  
Jeng-o Kim ◽  
Heeshin Kang ◽  
...  

Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 1174 ◽  
Author(s):  
Jian Luo ◽  
Chang Lin

In this study, we propose a real-time pedestrian detection system using a FPGA with a digital image sensor. Comparing with some prior works, the proposed implementation realizes both the histogram of oriented gradients (HOG) and the trained support vector machine (SVM) classification on a FPGA. Moreover, the implementation does not use any external memory or processors to assist the implementation. Although the implementation implements both the HOG algorithm and the SVM classification in hardware without using any external memory modules and processors, the proposed implementation’s resource utilization of the FPGA is lower than most of the prior art. The main reasons resulting in the lower resource usage are: (1) simplification in the Getting Bin sub-module; (2) distributed writing and two shift registers in the Cell Histogram Generation sub-module; (3) reuse of each sum of the cell histogram in the Block Histogram Normalization sub-module; and (4) regarding a window of the SVM classification as 105 blocks of the SVM classification. Moreover, compared to Dalal and Triggs’s pure software HOG implementation, the proposed implementation‘s average detection rate is just about 4.05% less, but can achieve a much higher frame rate.


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