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Imaging Sensor Technologies and Applications [Kõva köide]

Edited by (University of Manchester, Department of Electrical and Electronic Engineering, UK)
  • Formaat: Hardback, 536 pages, kõrgus x laius: 234x156 mm
  • Sari: Control, Robotics and Sensors
  • Ilmumisaeg: 07-Sep-2020
  • Kirjastus: Institution of Engineering and Technology
  • ISBN-10: 1785614975
  • ISBN-13: 9781785614972
Teised raamatud teemal:
Imaging Sensor Technologies and ApplicationsSuurem pilt
  • Formaat: Hardback, 536 pages, kõrgus x laius: 234x156 mm
  • Sari: Control, Robotics and Sensors
  • Ilmumisaeg: 07-Sep-2020
  • Kirjastus: Institution of Engineering and Technology
  • ISBN-10: 1785614975
  • ISBN-13: 9781785614972
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781785614972.html
Märksõnad:

This edited book presents state-of-the-art research on imaging sensors covering a wide frequency range and different sensing modalities and applications.



Imaging sensors are crucial for electronic imaging systems, including digital cameras, camera modules, medical imaging equipment, night vision equipment, radar and sonar, drones, and many others. This contributed book covers a wide range of frequency, sensing modalities and applications, including x-ray beam imaging sensors, optical scattering sensors, smart visual sensors in robotic systems, tuneable diode Laser absorption spectroscopy (TDLAS) sensors, light detection and ranging (LiDAR) sensors, microwave imaging sensors, electro-magnetic imaging with ultra-wideband (UWB) sensors, Synthetic aperture radar (SAR), electrical resistance tomography (ERT) sensors, electrical tomography for medical applications, electro-magnetic tomography (EMT) sensors, micro sensors for cell and blood imaging, and ultrasound imaging sensors.

Bringing together information on state-of-the-art research in the field, this book is a valuable resource for engineers, researchers, designers and developers, and advanced students and lecturers working on sensing, imaging, optics, photonics, medical imaging, instrumentation, measurement and electronics.

Preface xiii
Imaging sensor technologies and applications xvii
About the editor xix
1 X-ray beam imaging sensors 1(32)
Roelof van Silfhout
List of abbreviations
1(1)
1.1 Introduction
1(2)
1.2 Non-destructive X-ray beam monitoring
3(3)
1.2.1 Gas scattering
4(1)
1.2.2 Foil scattering
5(1)
1.3 Sensors
6(6)
1.3.1 Quadrant photodiode
7(1)
1.3.2 Lateral effect photodiode
8(1)
1.3.3 Image (pixel array) sensors
8(4)
1.4 X-ray beam imaging
12(4)
1.5 Pinhole/coded aperture X-ray camera
16(6)
1.5.1 Linearity
16(2)
1.5.2 Precision
18(2)
1.5.3 Beam imaging
20(2)
1.6 System implementation and description
22(2)
1.7 Results and discussion
24(4)
1.8 Summary
28(1)
References
28(5)
2 Optical scattering sensors 33(38)
Wu Zhou
Haitao Yu
Mingxu Su
Xiaoshu Cai
List of abbreviations
33(1)
2.1 Introduction
34(1)
2.2 Static light scattering
34(9)
2.2.1 Lorenz-Mie theory
34(4)
2.2.2 Rainbow technique
38(5)
2.3 Dynamic light scattering
43(5)
2.3.1 Principle of DLS
43(1)
2.3.2 Particle sizing system based on DLS
44(4)
2.4 RGB multi-wavelengths light extinction
48(10)
2.4.1 Measuring fine particle size with RGB three-wavelength bands light extinction
48(1)
2.4.2 Measurement principle of RGB three-wavelength bands light extinction method
49(8)
2.4.3 Experimental verification
57(1)
2.4.4 Conclusion
58(1)
2.5 Ultrasonic scattering
58(6)
2.5.1 Principle of ultrasonic scattering
59(1)
2.5.2 Data inversion for particle sizing
60(2)
2.5.3 Measurement system for ultrasonic attenuation
62(2)
2.6 Future prospects
64(1)
References
64(7)
3 Smart visual sensors in robotic systems 71(36)
Pooja Agrawal
Laxmidher Behera
List of abbreviations
71(1)
3.1 Introduction
71(3)
3.2 Camera models and calibration
74(3)
3.2.1 Camera models
74(2)
3.2.2 Camera calibration
76(1)
3.3 Visual servoing
77(3)
3.3.1 Position-based visual servoing
78(1)
3.3.2 Image-based visual servoing
79(1)
3.3.3 2-1/2-D visual servoing
80(1)
3.4 Visual servoing control
80(17)
3.4.1 Manipulator robot
80(3)
3.4.2 KSOM-based redundancy preserving network
83(3)
3.4.3 Inverse-forward adaptive scheme with a KSOM-based hint generator
86(4)
3.4.4 Inverse Jacobian matrix estimation using Kohonen's self-organising map
90(1)
3.4.5 Near-optimal controllers for input affine nonlinear systems using single network adaptive critic
91(2)
3.4.6 A single network adaptive critic-based redundancy resolution scheme for redundant manipulators
93(1)
3.4.7 Reinforcement learning-based optimal redundancy resolution directly from the vision space
94(3)
3.5 Autonomous ground robot
97(3)
3.5.1 Experimental setup and results
98(2)
3.6 Implementation issues
100(1)
3.7 Summary
100(1)
References
100(7)
4 CCD and CMOS sensors and their applications in flame measurement 107(46)
Gang Lu
List of abbreviations
107(1)
4.1 Introduction
108(1)
4.2 CCD and CMOS imaging sensors
108(19)
4.2.1 CCD sensor
109(11)
4.2.2 CMOS imaging sensors
120(2)
4.2.3 Special imaging sensors
122(3)
4.2.4 Camera interfaces
125(1)
4.2.5 Sizes of imaging sensor and lens
126(1)
4.2.6 Shutters
127(1)
4.3 Flame imaging and measurement
127(21)
4.3.1 Nature of flame
127(1)
4.3.2 Flame visualisation and measurement
128(2)
4.3.3 2D flame imaging
130(10)
4.3.4 3D flame imaging
140(7)
4.3.5 Flame chemiluminescence imaging
147(1)
4.4 Summary
148(1)
References
149(4)
5 Tunable diode Laser absorption spectroscopy (TDLAS) sensors 153(40)
Zhang Cao
Lijun Xu
List of abbreviations
153(1)
5.1 Introduction
154(1)
5.2 TDLAS sensor
155(9)
5.2.1 Principles for TDLAS sensors
157(3)
5.2.2 Laser control and emitting unit
160(1)
5.2.3 Data acquisition unit
161(1)
5.2.4 TDLAS tomographic system
162(2)
5.3 Total absorbance extraction and on-chip implementation
164(12)
5.3.1 DAS method
165(1)
5.3.2 On-chip implementation of DAS method
166(4)
5.3.3 WMS method
170(3)
5.3.4 On-chip implementation of WMS method
173(3)
5.4 Calibration of single path TDLAS sensor
176(6)
5.4.1 Performance evaluation
177(2)
5.4.2 Performance evaluation at high temperatures
179(3)
5.5 Image reconstruction for TDLAS tomography
182(2)
5.5.1 SART algorithm
182(1)
5.5.2 Tikhonov regularisation method
183(1)
5.5.3 Landweber method
183(1)
5.6 Case studies
184(5)
5.6.1 Case study 1: Acoustic excited flame monitoring
184(3)
5.6.2 Case study 2: Process monitoring for high-temperature wind tunnel
187(2)
5.7 Prospects and future work
189(1)
References
189(4)
6 Light detection and ranging (LiDAR) sensors 193(34)
Xiaolu Li
Lijun Xu
List of abbreviations
193(1)
6.1 Introduction
194(1)
6.2 TLS system
195(12)
6.2.1 Laser emitter
195(1)
6.2.2 Scanning unit
196(2)
6.2.3 Receiver
198(1)
6.2.4 Detector
199(1)
6.2.5 Ranging system
200(5)
6.2.6 Software
205(2)
6.3 TLS errors and self-calibration
207(12)
6.3.1 Angle errors model
207(2)
6.3.2 Self-calibration methods
209(3)
6.3.3 Feature points extraction
212(2)
6.3.4 Self-calibration results
214(1)
6.3.5 TLS ranging errors
215(4)
6.4 TLS applications on civil and agriculture
219(4)
6.4.1 Tunnel seepage detection
219(1)
6.4.2 Individual maize plant extraction
219(2)
6.4.3 Registration for urban structures
221(2)
6.5 Future prospects
223(1)
References
223(4)
7 Microwave imaging sensors 227(26)
Alessandro Fedeli
Matteo Pastorino
Andrea Randazzo
List of abbreviations
227(1)
7.1 Introduction
227(3)
7.2 Microwave imaging systems
230(4)
7.3 Antennas for microwave imaging
234(11)
7.3.1 Monopole and dipole antennas
235(3)
7.3.2 Folded structures
238(1)
7.3.3 Bowtie antenna
239(1)
7.3.4 Slot antennas
240(1)
7.3.5 Tapered slot and Vivaldi antennas
241(1)
7.3.6 Open waveguides
242(1)
7.3.7 Horn
243(1)
7.3.8 Patch
244(1)
7.3.9 Other sensor elements
245(1)
7.4 Future trend
245(1)
References
245(8)
8 Electro-magnetic imaging with ultra-wideband (UWB) sensors 253(44)
Mohd Zaid Abdullah
List of abbreviations
253(1)
8.1 Introduction
253(1)
8.2 Image reconstruction
254(9)
8.2.1 Forward problem
255(3)
8.2.2 Inverse problem
258(5)
8.3 Sensor and instrumentation system
263(16)
8.3.1 UWB antenna
263(12)
8.3.2 Data acquisition system
275(4)
8.4 Results and discussion
279(13)
8.4.1 Limited view geometry
279(13)
8.5 Summary
292(1)
References
293(4)
9 Synthetic aperture radar (SAR) 297(34)
Guangcai Sun
Mengdao Xing
Liang Guo
List of abbreviations
297(1)
9.1 Introduction
298(1)
9.2 Principle of synthetic aperture
298(6)
9.2.1 Range resolution
302(1)
9.2.2 Azimuth resolution
302(2)
9.3 Imaging principle and range Doppler algorithm
304(8)
9.3.1 Basic principles of SAR imaging
305(2)
9.3.2 Range Doppler algorithm
307(5)
9.4 Imaging modes
312(4)
9.4.1 Multi-mode unified signal model
313(1)
9.4.2 Signal property
314(2)
9.5 Multi-mode unified imaging method
316(10)
9.5.1 Fractional Fourier transformation (FrFT)
316(1)
9.5.2 Algorithm description
317(2)
9.5.3 Applications for Sliding Spotlight and TOPS SAR
319(5)
9.5.4 Applied to Stripmap and Spotlight SAR
324(1)
9.5.5 Real data results
324(2)
9.6 Summary
326(1)
References
327(4)
10 Electrical resistance tomography (ERT) sensors and applications 331(36)
Huaxiang Wang
List of abbreviations
331(1)
10.1 Introduction
332(3)
10.1.1 Forward problem of ERT
332(2)
10.1.2 Inverse problem of ERT
334(1)
10.2 Optimised design of ERT sensor
335(7)
10.2.1 Optimisation index of ERT sensor
338(1)
10.2.2 Excitation and measurement strategies
339(3)
10.3 Data acquisition system
342(8)
10.3.1 Sinewave generator
343(2)
10.3.2 Signal conditioning circuits
345(1)
10.3.3 Voltage-controlled current source
345(3)
10.3.4 Differential amplifiers
348(1)
10.3.5 Signal conditioning circuit
348(1)
10.3.6 Digital demodulation
349(1)
10.4 Image reconstruction
350(4)
10.4.1 Sensitivity/Jacobian matrix-based methods
351(3)
10.5 Applications of ERT
354(8)
10.5.1 Multi-phase flow measurement
354(3)
10.5.2 Volume fraction measurement of gas-liquid bubble column
357(2)
10.5.3 Fluidised bed reactor
359(1)
10.5.4 Milk processing
360(2)
10.6 Summary
362(1)
References
363(4)
11 Electrical tomography for medical applications 367(38)
Zhen Ren
Wuqiang Yang
List of abbreviations
367(1)
11.1 Introduction
368(1)
11.2 Breast imaging
369(6)
11.2.1 TUGEM measuring system
370(1)
11.2.2 Duke University's system
370(1)
11.2.3 Dartmouth EIT system
370(3)
11.2.4 Commercial EIT systems for breast cancer detection
373(1)
11.2.5 Wearable smart device-based EIT mammography
374(1)
11.3 Other cancer research: cervical, colorectal and prostates cancer
375(2)
11.3.1 Cervical cancer
375(1)
11.3.2 Colorectal cancer
376(1)
11.3.3 Prostate cancer
376(1)
11.4 Lung imaging
377(6)
11.5 Brain function imaging and neuroscience
383(2)
11.6 Image-based surgery
385(5)
11.6.1 Endodontic therapy
385(2)
11.6.2 Revision total hip replacement
387(3)
11.7 Summary
390(1)
References
390(15)
12 Electromagnetic tomography (EMT) sensors 405(24)
Wuliang Yin
List of abbreviations
405(1)
12.1 Introduction
405(3)
12.2 Forward problem and sensitivity maps
408(15)
12.2.1 Analytical solution for calculating sensitivity maps
408(3)
12.2.2 Simulation with a custom edge-element FEM solver
411(5)
12.2.3 Simulation with a custom BEM solver
416(6)
12.2.4 Simulation with a commercial software
422(1)
12.3 MIT hardware system design
423(1)
12.4 Typical applications
424(3)
12.5 Summary
427(1)
References
427(2)
13 Micro-sensors for cell and blood imaging 429(30)
Jiafeng Yao
Masahiro Takei
List of abbreviations
429(1)
13.1 Introduction
429(2)
13.2 Micro-sensors with different structures
431(1)
13.3 Noise reduction methods for micro-sensors
432(4)
13.3.1 Noise from macro- to micro-sensors
432(1)
13.3.2 Contact impedance
433(3)
13.4 Cell imaging
436(10)
13.4.1 Micro-fluidic sensors
436(1)
13.4.2 Simulation of cell distribution
437(3)
13.4.3 Cell imaging experiments
440(6)
13.5 Blood flow measurement
446(8)
13.5.1 Experimental setup and method
447(2)
13.5.2 Experimental results
449(5)
13.6 Future prospects
454(1)
References
455(4)
14 Ultrasound imaging sensors 459(36)
Jianguo Ma
Xiaoning Jiang
Lijun Xu
List of abbreviations
459(1)
14.1 Introduction
459(1)
14.2 Ultrasound wave
460(11)
14.2.1 Fundamentals of acoustic wave
460(4)
14.2.2 Ultrasound beams
464(4)
14.2.3 Reflection and scattering
468(1)
14.2.4 Attenuation
468(1)
14.2.5 Doppler shift
469(1)
14.2.6 Nonlinearities in ultrasound imaging
470(1)
14.3 Ultrasound sensors
471(12)
14.3.1 Piezoelectric ultrasound transducers
471(6)
14.3.2 Piezoelectric array
477(2)
14.3.3 Capacitive micro-machined ultrasound transducers
479(1)
14.3.4 Optical ultrasound sensors
480(3)
14.4 Ultrasound imaging
483(8)
14.4.1 Ultrasound imaging system
483(1)
14.4.2 Amplitude mode (A-mode) ultrasound imaging
484(1)
14.4.3 Brightness mode (B-mode) ultrasound imaging
485(1)
14.4.4 Motion mode (M-mode) ultrasound imaging
486(1)
14.4.5 Intravascular ultrasound (IVUS) imaging
487(2)
14.4.6 Doppler ultrasonography
489(1)
14.4.7 Harmonic imaging
490(1)
14.5 Summary
491(1)
References
491(4)
Index 495
Wuqiang Yang is a Fellow of the IEEE, Fellow of the IET and Fellow of the Institute of Measurement and Control. He spent 13 years at Tsinghua University in Beijing, as an undergraduate, MSc and PhD student and then as a lecturer. Since 1991, he has been working with UMIST and University of Manchester in the UK. He became a Professor in the Department of Electrical and Electronic Engineering in 2005. His main research interests include electrical capacitance tomography (ECT), instrumentation and multiphase flow measurement. He has published 400 papers and edited a book 'Sensor array', which is published by Intech. He is an Associate Editor of IEEE Trans. on Instrum. and Meas. and IET Sci., Meas. and Technol., editorial board member of several other journals (including Meas. Sci. and Technol. and Sensor Review), guest editor of many journal special issues and visiting professor at several other universities. He is one of the key organisers of the annual IEEE International Conference on Imaging Systems and Techniques. He was an IEEE IMS Distinguished Lecturer (2010-2016) and a JSPS Invitation Fellow (2016) and is a JSPS Bridge Fellow (2020). His biography has been included in Who's Who in the World since 2002.