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Biologically Inspired CMOS Image Sensor 2013 ed. [Pehme köide]

  • Formaat: Paperback / softback, 258 pages, kõrgus x laius: 235x155 mm, kaal: 4102 g, X, 258 p., 1 Paperback / softback
  • Sari: Studies in Computational Intelligence 461
  • Ilmumisaeg: 29-Jan-2015
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642444792
  • ISBN-13: 9783642444791
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  • Formaat: Paperback / softback, 258 pages, kõrgus x laius: 235x155 mm, kaal: 4102 g, X, 258 p., 1 Paperback / softback
  • Sari: Studies in Computational Intelligence 461
  • Ilmumisaeg: 29-Jan-2015
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642444792
  • ISBN-13: 9783642444791
This book presents a new approach for designing net zero energy buildings based on thermal discomfort minimization. The method helps a designer to automatically search for the optimal solution among a large set of building variants.

Biological systems are a source of inspiration in the development of small autonomous sensor nodes. The two major types of optical vision systems found in nature are the single aperture human eye and the compound eye of insects. The latter are among the most compact and smallest vision sensors. The eye is a compound of individual lenses with their own photoreceptor arrays. The visual system of insects allows them to fly with a limited intelligence and brain processing power. A CMOS image sensor replicating the perception of vision in insects is discussed and designed in this book for industrial (machine vision) and medical applications.

The CMOS metal layer is used to create an embedded micro-polarizer able to sense polarization information. This polarization information is shown to be useful in applications like real time material classification and autonomous agent navigation. Further the sensor is equipped with in pixel analog and digital memories which allow variation of the dynamic range and in-pixel binarization in real time. The binary output of the pixel tries to replicate the flickering effect of the insect’s eye to detect smallest possible motion based on the change in state. An inbuilt counter counts the changes in states for each row to estimate the direction of the motion. The chip consists of an array of 128x128 pixels, it occupies an area of 5 x 4 mm2 and it has been designed and fabricated in an 180nm CMOS CIS process from UMC.



This book presents a new approach for designing net zero energy buildings based on thermal discomfort minimization. The method helps a designer to automatically search for the optimal solution among a large set of building variants.
1 Introduction
1(12)
1.1 Perception of Vision
1(3)
1.2 Motivation
4(4)
1.2.1 Wide Field of View
6(1)
1.2.2 Motion Detection
6(1)
1.2.3 High Sensitivity to Low Light Intensity
7(1)
1.2.4 Polarization
7(1)
1.3 Book Organization
8(5)
References
10(3)
2 Natural and Artificial Compound Eye
13(36)
2.1 Natural Compound Eye
13(5)
2.1.1 Apposition Eye
15(1)
2.1.2 Superposition Eye
16(2)
2.2 Properties of Compound Eye
18(8)
2.3 Polarization Vision in Compound Eyes
26(2)
2.4 Artificial Compound Eye
28(9)
2.4.1 Design Consideration of an Artificial Compound Eye
32(4)
2.4.2 Design of Artificial Compound Eye
36(1)
2.5 Micro-optics Design
37(9)
2.5.1 Image Mapping and Distortion Correction
43(3)
2.6 Summary
46(3)
References
47(2)
3 Design of a CMOS Image Sensor
49(56)
3.1 Introduction
49(2)
3.2 Photodetector
51(6)
3.3 Basic CMOS Image Sensor Architecture
57(7)
3.3.1 Passive Pixel Sensor
57(1)
3.3.2 Active Pixel Sensor
58(4)
3.3.3 Digital Pixel Sensor
62(2)
3.4 CMOS Image Sensor Performance
64(9)
3.4.1 Quantum Efficiency and Spectral Responsivity
64(2)
3.4.2 Dynamic Range and Signal-to-Noise Ration (SNR)
66(2)
3.4.3 Pixel Conversion Gain
68(1)
3.4.4 Dark Current
68(2)
3.4.5 Noise in CMOS Image Sensor
70(3)
3.5 CMOS Image Sensor Peripherals
73(5)
3.5.1 Addressing
73(1)
3.5.2 Column Processing Circuits
74(2)
3.5.3 Analog-to-Digital Conversion
76(2)
3.6 Designed Sensor Overview
78(19)
3.6.1 Pixel Architecture
79(2)
3.6.2 Pixel Operation
81(6)
3.6.3 Pixel Layout
87(1)
3.6.4 Row/Column Addressing Logic
88(3)
3.6.5 Analog Signal Chain
91(4)
3.6.6 Digital Signal Chain
95(2)
3.7 Image Sensor Characterization
97(5)
3.7.1 Test Setup
98(1)
3.7.2 Measurements
99(3)
3.8 Summary
102(3)
References
103(2)
4 Design of a CMOS Polarization Sensor
105(52)
4.1 Polarization Vision
105(1)
4.2 Polarization of Light - Basics
106(9)
4.2.1 Polarization of Light from an Unpolarized Beam
108(3)
4.2.2 Polarization of Light - Representation
111(4)
4.3 Polarization Cameras
115(3)
4.4 Wire-grid Polarizer
118(19)
4.4.1 Fabrication of Wire-grid Polarizer
122(2)
4.4.2 Transmittance Efficiency and Extinction Ratio of Wire-grid Polarizers
124(13)
4.5 Design of a Polarization Sensor
137(2)
4.6 Polarization Measurements
139(6)
4.6.1 Measurement Setup
139(3)
4.6.2 Analog Polarization Measurements
142(3)
4.7 Wavelength Selection Using Metal Grid
145(7)
4.8 Summary
152(5)
References
154(3)
5 Material Classification Using CMOS Polarization Sensor
157(28)
5.1 Introduction
157(2)
5.2 Polarization and Fresnel Coefficients
159(7)
5.2.1 Polarization Properties of a Reflected Light
160(4)
5.2.2 Fresnel Reflectance Model
164(2)
5.3 Material Classification Measurements
166(11)
5.3.1 Measurement Setup
167(1)
5.3.2 Polarization Transmittance
167(3)
5.3.3 Material Classification Using the Degree of Polarization
170(2)
5.3.4 Material Classification Using the Stokes Parameters
172(2)
5.3.5 Material Classification Using Polarization Fresnel Ratio
174(3)
5.4 Metal Classification
177(5)
5.4.1 Metal Classification Using PFR
179(2)
5.4.2 Metal Classification Using Degree of Polarization
181(1)
5.5 Summary
182(3)
References
184(1)
6 Navigation Using CMOS Polarization Sensor
185(30)
6.1 Introduction
185(3)
6.2 Celestial Compass Based on Skylight Polarization
188(3)
6.3 Navigation Using Polarized Light by Insects
191(2)
6.4 Navigation Using Polarized Light for Autonomous Agents
193(4)
6.5 Polarization Based Compass
197(5)
6.5.1 Measurement Setup
197(1)
6.5.2 Measurement Results
197(5)
6.6 Incoming Light Ray Direction Detection and Sun Position Detection
202(5)
6.6.1 Measurement Setup
202(1)
6.6.2 Measurement Results for Incoming Light Ray Directions
203(4)
6.7 Real-Time Implementation of Navigation Compass
207(4)
6.8 Summary
211(4)
References
212(3)
7 Motion Detection and Digital Polarization
215(32)
7.1 Motion Detection
215(5)
7.1.1 Motion Detection - Models
218(2)
7.2 Motion Detection - Differential Imaging
220(3)
7.3 Motion Detection - Optical Flow
223(10)
7.3.1 Motion in Vertical Direction - Collision Detection
224(7)
7.3.2 Motion in Horizontal Direction
231(2)
7.4 Illumination Invariant and High Dynamic Range Motion Detection
233(6)
7.5 Digital Polarization
239(3)
7.6 Summary
242(5)
References
243(4)
8 Future Works
247(6)
8.1 Future Works
247(6)
8.1.1 Wide Field of View Imaging System with Polarization Sensitivity
247(2)
8.1.2 High Angular Resolution Imaging System with Polarization Sensitivity
249(3)
References
252(1)
Summary 253(4)
Acknowledgments 257