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Bio-inspired artificial vision and neuromorphic imaging devices : 생체모방 인공 시각 및 뉴로몰픽 이미징 디바이스

DC Field Value Language
dc.contributor.advisor김대형-
dc.contributor.author김민성-
dc.date.accessioned2024-05-31T18:02:16Z-
dc.date.available2024-05-31T18:02:16Z-
dc.date.issued2022-
dc.identifier.other000000169563-
dc.identifier.urihttps://hdl.handle.net/10371/204045-
dc.identifier.urihttps://dcollection.snu.ac.kr/common/orgView/000000169563ko_KR
dc.description학위논문(박사) -- 서울대학교대학원 : 공과대학 화학생물공학부(에너지환경 화학융합기술전공), 2022. 2. 김대형.-
dc.description.abstractIn the past decade, significant advancements have been accomplished in image sensor technology for achieving efficient object detection with high signal to noise ratio that consists of image acquisition and image data processing. This advancement in image capturing and image processing has promoted major development in the field of mobile electronics and applications in machine vision. However, since the conventional imaging technology uses a planar image sensor, a multi-lens structure is required for wide visual field, high-quality and aberration-free imaging. This multi-lens structure makes the camera module large and bulky, which hinders the miniaturization of overall system. In this context, by mimicking a single lens and a curved retina structure of natural eyes that evolved to be optimized for their habitat, such technological limitations can be efficiently resolved. Also, by mimicking their strategies to obtain high quality visual information in their habitat, specialized camera with high object detectability and high signal to noise ratio can be developed. Here, we describe three different types of the next-generation bio-inspired artificial vision systems.
Firstly, we develop a novel wide-field-of-view camera by integrating a tailored monocentric lens and a hemispherical silicon nanorod photodiode array inspired by the eye of an aquatic animal. Such an aquatic-vision-inspired camera offers the wide FoV, miniaturized module size, minimal optical aberration, deep depth-of-field, facile accommodation, and enhanced light sensitivity in one simple integrated device. Theoretical analyses and imaging demonstrations have corroborated the validity of the developed artificial vision system.
Secondly, inspired by the cuttlefish-eye, we develop a high-contrast polarizing camera that specializes in the low-contrast shallow-water environment. By mimicking the W-shaped pupil of cuttlefish-eye, an artificial vision system compensates uneven vertical light profile. In addition, the cylindrical silicon photodiode array which contains high-density belt-like pixel profile, allowing to have wide horizontal-field-of-view inspired by curved retina of cuttlefish-eye. The flexible, linear polarizing film on top of the cylindrical silicon photodiode array enables high-contrast polarization imaging.
Thirdly, inspired by the structural and functional features of the human visual recognition system, we report a curved neuromorphic image sensor array with reduced noise by employing a heterostructure of MoS2 and poly(1,3,5-trimethyl-1,3,5-trivinyl cyclotrisiloxane) (pV3D3). Such an artificial vision system features the photon-triggered electrical responses similar to the synaptic plasticity of neural network that consists of short-term plasticity and long-term potentiation. Such photon-triggered synaptic plasticity of the MoS2-pV3D3 phototransistor was experimentally and theoretically analyzed. The developed system can efficiently recognize the original image by reducing the noises of input images.		-
dc.description.tableofcontentsAbstract i
Contents iv
List of Figures vi
Chapter 1. Introduction 1
1.1 Evolution of efficient imaging and image processing technologies 1
1.2 Bio-inspired artificial vision system inspired by the chambered eye 5
1.3 Neuromorphic image processing devices 9
1.4 Conclusion 19
1.5 Reference 20
Chapter 2. An aquatic-vision-inspired camera based on a monocentric lens and a silicon nanorod photodiode array 24
2.1 Introduction 24
2.2 Experimental Section 29
2.3 Results and discussion 35
2.4 Conclusion 56
2.5 Reference 57
Chapter 3. Cuttlefish-eye-inspired artificial vision for high-contrast and high-acuity imaging in the shallow-water environment 60
3.1 Introduction 60
3.2 Experimental Section 63
3.3 Results and discussion 66
3.4 Conclusion 74
3.5 Reference 75
Chapter 4. Curved neuromorphic image sensor array using a MoS2-organic heterostructure inspired by the human visual recognition system 76
4.1 Introduction 76
4.2 Experimental Section 78
4.3 Results and discussion 81
4.4 Conclusion 96
4.5 Reference 97

List of Figures
Chapter 1 4
Figure 1.1. Various imaging devices and image processing devices inspired by the visual system of human. 4
Figure 1.2. Various human-eye-type imaging system. 8
Figure 1.3. The memristor crossbar array and its major applications. 12
Figure 1.4. The synaptic device integrated with the photodetector and its major applications. 13
Figure 1.5. Neuromorphic vision sensor. 16
Figure 1.6. Neuromorphic vision sensors for the pre-processing applications. 17
Figure 1.7. Neuromorphic vision sensors for the post-processing applications. 18
Chapter 2 27
Figure 2.1. Compound-type-eye structure. 27
Figure 2.2. An aquatic-type-eye structure. 28
Figure 2.3. Fabrication process of the monocentric lens. 32
Figure 2.4. Surface profiles of the aperture (a) and the SF16 (b). 33
Figure 2.5. Doping profiles of boron (a) and phosphorous (b). 34
Figure 2.6. Photograph of aquatic animal and schematics of its anatomy. 37
Figure 2.7. Schematic illustration of aquatic eye. 38
Figure 2.8. Optical simulation results of monocentric lens with hemispherical retina (a), Schematic illustration showing deep depth of field vision of aquatic vision (b). 39
Figure 2.9. Schematic illustration of visual accommodation process of the aquatic vision (a), Schematic illustration of visual accommodation process of the human vision (b). 40
Figure 2.10. Schematic illustration of an aquatic-vision-inspired artificial vision (a), Schematic illustration of exploded view of the mo-lens (b). 43
Figure 2.11. Various optical simulations of mo-lens. 44
Figure 2.12. Photograph of hemispherical silicon nanorod photodiode array on the flat substrate and on the curved substrate (inset). 47
Figure 2.13. FEA results of silicon nanorod photodiode array. 48
Figure 2.14. Three-dimensional AFM image of the silicon nanorod photodiode (a), Cross-sectional TEM image of the silicon nanorod photodiode (b). 49
Figure 2.15. Graph showing absorption of bare silicon and silicon nanorod photodiode as a function of wavelength. 50
Figure 2.16. Graph showing dark current and photo current of the silicon nanorod photodiode with and without Al2O3 passivation. 51
Figure 2.17. I-V characteristics curve of the silicon nanorod photodiode. 52
Figure 2.18. Photograph of developed bio-inspired camera (a), Imaging demonstration result showing wide visual field using such a camera (b). 54
Figure 2.19. Imaging demonstration result showing deep DoF (a), and facile accommodation (b). 55
Chapter 3 62
Figure 3.1. Schematic illustration of shallow-water environment (a), schematic illustration of anatomy of cuttlefish-eye (b). 62
Figure 3.2. Schematic illustration showing fabrication process of cylindrical silicon photodiode array. 65
Figure 3.3. Schematic illustration showing the integrated lens system (a), exploded view of the integrated lens system. 67
Figure 3.4. Graph showing spot radii of circular pupil and W-shaped pupil as a function of horizontal incident angle. 68
Figure 3.5. Photograph of silicon photodiode array. 71
Figure 3.6. I-V curves. 72
Figure 3.7. Schematic illustration of the overall optical system. 73
Chapter 4 83
Figure 4.1. Schematic illustrations showing human visual recognition system (a), the developed curved neuromorphic imaging system that consists of a plano-convex lens and cNISA (b). 83
Figure 4.2. Schematic illustration showing individual pixel of cNISA (a), optical microscope image of individual pixel of cNISA (b), TEM image individual pixel of cNISA (c). 86
Figure 4.3. Graphs showing photocurrent of cNISA as a function of time. 87
Figure 4.4. Graph showing photocurrent (a.u.) as a function of time. 88
Figure 4.5. Graph showing photocurrent (a.u.) as a function of time (a), graph showing An/A1 as a function of the number of optical pulses (b). 89
Figure 4.6. Photograph of integrated system that consists of cNISA, plano-convex lens, mold, and housing (a), schematic illustration of exploded view of overall system (b). 92
Figure 4.7. Photograph of the cNISA transfer-printed on the hemispherical PDMS mold. 93
Figure 4.8. Simulation results for first principal strain distribution. 94
Figure 4.9. Neuromorphic imaging demonstration results using the cNISA. 95		-
dc.format.extentix, 100-
dc.language.isoeng-
dc.publisher서울대학교 대학원-
dc.subjectBio-inspired artificial vision-
dc.subjectArtificial synapse-
dc.subjectspecialty camera-
dc.subjectCurved image sensor-
dc.subjectNeuromorphic vision sensor-
dc.subjectFlexible electronics-
dc.subject.ddc660.6-
dc.titleBio-inspired artificial vision and neuromorphic imaging devices-
dc.title.alternative생체모방 인공 시각 및 뉴로몰픽 이미징 디바이스-
dc.typeThesis-
dc.typeDissertation-
dc.contributor.AlternativeAuthorMin Sung Kim-
dc.contributor.department공과대학 화학생물공학부(에너지환경 화학융합기술전공)-
dc.description.degree박사-
dc.date.awarded2022-02-
dc.identifier.uciI804:11032-000000169563-
dc.identifier.holdings000000000047▲000000000054▲000000169563▲-
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