Relevant bibliographies by topics / Smartphone Camera Quality

Academic literature on the topic 'Smartphone Camera Quality'

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Published: 14 March 2023

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Journal articles on the topic "Smartphone Camera Quality"

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Gupta, Shubhi, Prakash Srivastava, and Ashutosh Gupta. "Portable Smart Healthcare Approach for Earlier Stage Eye Tests for Diabetic Retinopathy Detection." International Journal of Information Retrieval Research 11, no. 2 (April 2021): 53–68. http://dx.doi.org/10.4018/ijirr.2021040104.

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High-quality, wide field retinal imaging is an effective method of retinal disease screening that is preventable and endangers vision. Retinal smartphone-based cameras promise to increase retinal imagery access, but variable image quality and restricted field of view can restrict their usefulness. This article discusses how to build a fundus camera based on smartphones that is capable of photographing the central retina and the peripheral retina up to the plana pars. It is a cost-effective alternative to the fundus camera.
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Wu, Fei, Songping Wu, and Mark Hayter. "MIPI Camera: Opportunities, Challenges and Solutions for Chromebook Cameras." Electronic Imaging 2021, no. 9 (January 18, 2021): 207–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.9.iqsp-207.

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Smartphone cameras revolutionized for at least two generations in the past decade; i.e. megapixel enthusiasm and multi-camera combination. However, most laptops are still with low resolution fixed focused webcam cameras. The story could have changed recently. The COVID-19 pandemic keeps people working from home; therefore, video conferencing becomes part of the new normal of daily life. The camera quality of laptop computers is in the spotlight when users join video conferences using their laptops webcam. We are working on a MIPI camera solution to drive the Chromebook webcam quality with minimum impact of cost. There are several challenges by porting the current smartphone MIPI camera technology to Chromebook directly: miniature module size and challenge of the hardware product design, limited ISP. There is also no complete evaluation criterion to video conferencing quality. We will discuss each aspect one by one.
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Masiero, A., A. Guarnieri, and A. Vettore. "ASSESSMENT OF A PORTABLE TOF CAMERA AND COMPARISON WITH SMARTPHONE STEREO VISION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W17 (November 29, 2019): 187–93. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w17-187-2019.

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Abstract. Nowadays time-of-flight (ToF) cameras and multiple RGB cameras are being embedded in an increasing number of high-end smartphones: despite their integration in mobile devices is mostly motivated by photographic applications, their availability can be exploited to enable 3D reconstructions directly on smartphones. Furthermore, even when a ToF camera is not embedded in a smartphone, low cost solutions are available on the market in order to easily provide standard mobile devices with a lightweight and extremely portable ToF camera. This work deals with the assessment of a low cost ToF camera, namely Pico Zense DCAM710, which perfectly fits with the above description. According to the results obtained in the considered tests, the ranging error (precision) of the DCAM710 camera increases linearly approximately up to the nominal maximum range in the considered working mode, up to approximately 1 cm. Despite the device allows to acquire measurements also at larger ranges, the measurement quality significantly worsen. After assessing the main characteristics of such ToF camera, this paper aims at comparing its 3D reconstruction ability with that of a smartphone stereo vision system. In particular, the comparison of a 3D reconstruction obtained with stereo vision from images acquired with an LG G6 shows that the stereo reconstruction leads to a much larger point cloud. However, points generated by the ToF camera are more homogeneously distributed, and they seem to slightly better describe the real geometry of the reconstructed object. The combination of such two technologies, which will be investigated in our future work, can potentially lead to a denser cloud with respect to the ToF camera, while preserving a reasonable accuracy.
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Larosa, Fati Gratianus Nafiri, and Ofelius Laia. "ANALISIS QUALITY OF SERVICE (QoS) LIVE STREAMING WIRELESS IP CAMERA XONZ BERBASIS SMARTPHONE ANDROID." METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi 5, no. 2 (September 10, 2019): 17–24. http://dx.doi.org/10.46880/mtk.v5i2.422.

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Quality of Service (QoS) on Live Streaming has the main parameters, namely bandwidth, jitter, loss and delay, which are measured on the implementation of Wireless IP Camera based on Android Smartphone. The test tools used iperf and ping software, to capture data packets. The network design in this study uses Xonz Wireless IP Camera, wifi router, Server/Laptop and Android Smartphone to monitor or access the services provided. Surveillance/reconnaissance or surveillance by accessing live streaming can be done from anywhere as long as there is still an intranet network. wifi router provides DHCP service, Server/Laptop provides a Virtual Machine using MS Windows Server 2003 Operating System. Web Server is not installed on Real Machine but on Virtual Machine. The smartphone used has the Android Operating System version 4.4.2. IP Camera Xonz model XZ-12Z-HR/W has one major drawback that it can only be accessed via Internet Explorer Browser which can only run on MS Windows Operating System. Some applications that are already available on Google Play and installed on Android Smartphones cannot detect the Wireless IP Camera. The outcome or impact of this research is the creation of a simple Live Streaming application that can be accessed by all browsers on all platforms including Android Smartphones. Measurements were made using iperf and ping. The results showed that the Xonz IP Camera can still be used for mobile room monitoring as far as a maximum of about 20 m from the wifi router and still meets the standard QoS values ​​set by TIPHON and ITU-T G.114.
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Saif, Wahib, and Adel Alshibani. "Smartphone-Based Photogrammetry Assessment in Comparison with a Compact Camera for Construction Management Applications." Applied Sciences 12, no. 3 (January 20, 2022): 1053. http://dx.doi.org/10.3390/app12031053.

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Close-range photogrammetry (CRP) has proven to be a remarkable and affordable technique for data modeling and measurements extraction in construction management applications. Nevertheless, it is important to aim for making CRP more accessible by using smartphones on-site directly without a pre-calibration procedure. This study evaluated the potential of smartphones as data acquisition tools in comparison with compact cameras based on the quality and accuracy of their photogrammetric results in extracting geometrical measurements (i.e., surface area and volume). Two concrete specimens of regular shapes (i.e., beam and cylinder) along with an irregular-shaped sand pile were used to conduct this study. The datasets of both cameras were analyzed and compared based on lens distortions, image residuals, and projections multiplicity. Furthermore, the photogrammetric models were compared according to various quality criteria, processing time, and memory utilization. Though both cameras were not pre-calibrated, they both provided highly accurate geometrical estimations. The volumetric estimation error ranged from 0.37% to 2.33% for the compact camera and 0.67% to 3.19% for the smartphone. For surface area estimations, the error ranged from 0.44% to 0.91% for the compact camera and 0.50% to 1.89% for the smartphone. Additionally, the smartphone data required less processing time and memory usage with higher applicability compared with the compact camera. The implication of these findings is that they provide professionals in construction management with an assessment of a more direct and cost-effective 3D data acquisition tool with a good understanding of its reliability. Moreover, the assessment methodology and comparison criteria presented in this study can assist future research in conducting similar studies for different capturing devices in construction management applications. The findings of this study are limited to small quantification applications. Therefore, it is recommended to conduct further research that assesses smartphones as a photogrammetric data acquisition tool for larger construction elements or tracking ongoing construction activities that involve measurements estimation.
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Gao, Min, Junsheng Li, Fangfang Zhang, Shenglei Wang, Ya Xie, Ziyao Yin, and Bing Zhang. "Measurement of Water Leaving Reflectance Using a Digital Camera Based on Multiple Reflectance Reference Cards." Sensors 20, no. 22 (November 18, 2020): 6580. http://dx.doi.org/10.3390/s20226580.

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With the development of citizen science, digital cameras and smartphones are increasingly utilized in water quality monitoring. The smartphone application HydroColor quantitatively retrieves water quality parameters from digital images. HydroColor assumes a linear relationship between the digital pixel number (DN) and incident radiance and applies a grey reference card to derive water leaving reflectance. However, image DNs change with incident light brightness non-linearly, according to a power function. We developed an improved method for observing and calculating water leaving reflectance from digital images based on multiple reflectance reference cards. The method was applied to acquire water, sky, and reflectance reference card images using a Cannon 50D digital camera at 31 sampling stations; the results were validated using synchronously measured water leaving reflectance using a field spectrometer. The R2 for the red, green, and blue color bands were 0.94, 0.95, 0.94, and the mean relative errors were 27.6%, 29.8%, 31.8%, respectively. The validation results confirm that this method can derive accurate water leaving reflectance, especially when compared with the results derived by HydroColor, which systematically overestimates water leaving reflectance. Our results provide a more accurate theoretical foundation for quantitative water quality monitoring using digital and smartphone cameras.
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Sirmacek, Beril, Roderik Lindenbergh, and Jinhu Wang. "QUALITY ASSESSMENT AND COMPARISON OF SMARTPHONE AND LEICA C10 LASER SCANNER BASED POINT CLOUDS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 15, 2016): 581–86. http://dx.doi.org/10.5194/isprs-archives-xli-b5-581-2016.

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3D urban models are valuable for urban map generation, environment monitoring, safety planning and educational purposes. For 3D measurement of urban structures, generally airborne laser scanning sensors or multi-view satellite images are used as a data source. However, close-range sensors (such as terrestrial laser scanners) and low cost cameras (which can generate point clouds based on photogrammetry) can provide denser sampling of 3D surface geometry. Unfortunately, terrestrial laser scanning sensors are expensive and trained persons are needed to use them for point cloud acquisition. A potential effective 3D modelling can be generated based on a low cost smartphone sensor. Herein, we show examples of using smartphone camera images to generate 3D models of urban structures. We compare a smartphone based 3D model of an example structure with a terrestrial laser scanning point cloud of the structure. This comparison gives us opportunity to discuss the differences in terms of geometrical correctness, as well as the advantages, disadvantages and limitations in data acquisition and processing. We also discuss how smartphone based point clouds can help to solve further problems with 3D urban model generation in a practical way. We show that terrestrial laser scanning point clouds which do not have color information can be colored using smartphones. The experiments, discussions and scientific findings might be insightful for the future studies in fast, easy and low-cost 3D urban model generation field.
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Sirmacek, Beril, Roderik Lindenbergh, and Jinhu Wang. "QUALITY ASSESSMENT AND COMPARISON OF SMARTPHONE AND LEICA C10 LASER SCANNER BASED POINT CLOUDS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 15, 2016): 581–86. http://dx.doi.org/10.5194/isprsarchives-xli-b5-581-2016.

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3D urban models are valuable for urban map generation, environment monitoring, safety planning and educational purposes. For 3D measurement of urban structures, generally airborne laser scanning sensors or multi-view satellite images are used as a data source. However, close-range sensors (such as terrestrial laser scanners) and low cost cameras (which can generate point clouds based on photogrammetry) can provide denser sampling of 3D surface geometry. Unfortunately, terrestrial laser scanning sensors are expensive and trained persons are needed to use them for point cloud acquisition. A potential effective 3D modelling can be generated based on a low cost smartphone sensor. Herein, we show examples of using smartphone camera images to generate 3D models of urban structures. We compare a smartphone based 3D model of an example structure with a terrestrial laser scanning point cloud of the structure. This comparison gives us opportunity to discuss the differences in terms of geometrical correctness, as well as the advantages, disadvantages and limitations in data acquisition and processing. We also discuss how smartphone based point clouds can help to solve further problems with 3D urban model generation in a practical way. We show that terrestrial laser scanning point clouds which do not have color information can be colored using smartphones. The experiments, discussions and scientific findings might be insightful for the future studies in fast, easy and low-cost 3D urban model generation field.
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Meinich-Bache, Øyvind, Kjersti Engan, Tonje Søraas Birkenes, and Helge Myklebust. "Real-Time Chest Compression Quality Measurements by Smartphone Camera." Journal of Healthcare Engineering 2018 (October 28, 2018): 1–12. http://dx.doi.org/10.1155/2018/6241856.

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Out-of-hospital cardiac arrest (OHCA) is recognized as a global mortality challenge, and digital strategies could contribute to increase the chance of survival. In this paper, we investigate if cardiopulmonary resuscitation (CPR) quality measurement using smartphone video analysis in real-time is feasible for a range of conditions. With the use of a web-connected smartphone application which utilizes the smartphone camera, we detect inactivity and chest compressions and measure chest compression rate with real-time feedback to both the caller who performs chest compressions and over the web to the dispatcher who coaches the caller on chest compressions. The application estimates compression rate with 0.5 s update interval, time to first stable compression rate (TFSCR), active compression time (TC), hands-off time (TWC), average compression rate (ACR), and total number of compressions (NC). Four experiments were performed to test the accuracy of the calculated chest compression rate under different conditions, and a fifth experiment was done to test the accuracy of the CPR summary parameters TFSCR, TC, TWC, ACR, and NC. Average compression rate detection error was 2.7 compressions per minute (±5.0 cpm), the calculated chest compression rate was within ±10 cpm in 98% (±5.5) of the time, and the average error of the summary CPR parameters was 4.5% (±3.6). The results show that real-time chest compression quality measurement by smartphone camera in simulated cardiac arrest is feasible under the conditions tested.
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Al Husaini, Mohammed Abdulla Salim, Mohamed Hadi Habaebi, Teddy Surya Gunawan, and Md Rafiqul Islam. "Self-Detection of Early Breast Cancer Application with Infrared Camera and Deep Learning." Electronics 10, no. 20 (October 18, 2021): 2538. http://dx.doi.org/10.3390/electronics10202538.

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Breast cancer is the most common cause of death in women around the world. A new tool has been adopted based on thermal imaging, deep convolutional networks, health applications on smartphones, and cloud computing for early detection of breast cancer. The development of the smart app included the use of Mastology Research with the Infrared Image DMR-IR database and the training of the modified version of deep convolutional neural network model inception V4 (MV4). In addition to designing the application in a graphical user interface and linking it with the AirDroid application to send thermal images from the smartphone to the cloud and to retrieve the suggestive diagnostic result from the cloud server to the smartphone. Moreover, to verify the proper operation of the app, a set of thermal images was sent from the smartphone to the cloud server from different distances and image acquisition procedures to verify the quality of the images. Four effects on the thermal image were applied: Blur, Shaken, Tilted, and Flipping were added to the images to verify the detection accuracy. After conducting repeated experiments, the classification results of early detection of breast cancer, generated from the MV4, illustrated high accuracy performance. The response time achieved after the successful transfer of diagnostic results from the smartphone to the cloud and back to the smartphone via the AirDroid application is six seconds. The results show that the quality of thermal images did not affect by different distances and methods except in one method when compressing thermal images by 5%, 15%, and 26%. The results indicate 1% as maximum detection accuracy when compressing thermal images by 5%, 15%, and 26%. In addition, the results indicate detection accuracy increased in Blurry images and Shaken images by 0.0002%, while diagnostic accuracy decreased to nearly 11% in Tilted images. Early detection of breast cancer using a thermal camera, deep convolutional neural network, cloud computing, and health applications of smartphones are valuable and reliable complementary tools for radiologists to reduce mortality rates.
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Book chapters on the topic "Smartphone Camera Quality"

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Ko, Chia-Yin, Fang-Yie Leu, and I.-Tsen Lin. "Using a Smartphone as a Track and Fall Detector." In E-Health and Telemedicine, 922–44. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8756-1.ch047.

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This chapter proposes a smartphone-based system for both indoor and outdoor monitoring of people with dementia. The whole system comprises wandering detection, safety-zone monitoring, fall detection, communication services, alert notifications, and emergency medical services. To effectively track the elderly, the proposed system uses a smartphone camera to take real-time pictures along the user's path as he or she moves about. Those photos, accompanied with time and GPS signals, are delivered to and stored on the Cloud system. When necessary, family caregivers can download those data to quickly find a way to help the elderly individual. Additionally, this study uses tri-axial accelerometers to examine falls. To assure individuals' data is safeguarded appropriately, an RSA method has been adopted by the system to encrypt stored data. This reliable and minimally intrusive system provides people with dementia with an opportunity to maintain their social networks and to improve their quality of lives.
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Ko, Chia-Yin, Fang-Yie Leu, and I.-Tsen Lin. "Using a Smartphone as a Track and Fall Detector." In Advanced Technological Solutions for E-Health and Dementia Patient Monitoring, 272–95. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-7481-3.ch011.

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This chapter proposes a smartphone-based system for both indoor and outdoor monitoring of people with dementia. The whole system comprises wandering detection, safety-zone monitoring, fall detection, communication services, alert notifications, and emergency medical services. To effectively track the elderly, the proposed system uses a smartphone camera to take real-time pictures along the user's path as he or she moves about. Those photos, accompanied with time and GPS signals, are delivered to and stored on the Cloud system. When necessary, family caregivers can download those data to quickly find a way to help the elderly individual. Additionally, this study uses tri-axial accelerometers to examine falls. To assure individuals' data is safeguarded appropriately, an RSA method has been adopted by the system to encrypt stored data. This reliable and minimally intrusive system provides people with dementia with an opportunity to maintain their social networks and to improve their quality of lives.
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R., Vishalakshi G., Gopala Krishna, and Hanumantha Raju. "Wavelet Energy-Based Adaptive Retinex Algorithm for Low Light Mobile Video Enhancement." In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 16–39. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-7524-9.ch002.

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In today's world, smartphones are ubiquitous and feature high-quality cameras and video recording capabilities. The camera shake, shadows, or other environmental factors lead to poor video, even in low-lighting situations with a high-end camera. To preserve and enhance low-light mobile video, a wavelet energy-based adaptive retinex algorithm is proposed. The first step in the method is to extract frames from the composite video before it is fed into the algorithm in HSV space. The authors then apply the wavelet energy-based adaptive retinex algorithm to the dynamic range-extended value channel. Lighting conditions that cause video degradation are restored adaptively to their natural brightness. A color restoration technique that improves the conventional retinex method fixes the gray world violation problem. Wavelet energy is used as a metric in concurrence with the retinex algorithm to objectively validate image enhancement quality. An experimental work of more than 300 still images and videos show that the proposed technique outperforms the current state of the art.
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Hein, Daniel, and Hossein Saiedian. "Reasoning Qualitatively about Handheld Multimedia Framework Quality Attributes." In Digital Multimedia, 825–40. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3822-6.ch041.

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Today's mobile handheld devices, such as smartphones and action cameras, are well equipped for a wide range of multimedia and context-aware tasks. Such tasks can leverage traditional services like streaming audio and video as well as newer services like sensor fusion. Ubiquitous network access, coupled with an increasingly sophisticated mixture of device-based hardware and software, is enabling context-aware applications at an unprecedented rate. The objective of this chapter is to discuss specific quality attributes with respect to device-side software architectures providing these multimedia and sensor capabilities. This chapter focuses specifically on device-side client architectures rather than network or server architectures. Specific domain requirements and quality attributes are first derived through a synthesis of current research and industry trends, and subsequently analyzed. The analysis reveals some qualitative results that seem unintuitive at first glance but that become more understandable when provided with rationale relative to the handheld domain context.
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Hein, Daniel, and Hossein Saiedian. "Reasoning Qualitatively about Handheld Multimedia Framework Quality Attributes." In Handbook of Research on Innovations in Systems and Software Engineering, 731–45. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6359-6.ch028.

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Today's mobile handheld devices, such as smartphones and action cameras, are well equipped for a wide range of multimedia and context-aware tasks. Such tasks can leverage traditional services like streaming audio and video as well as newer services like sensor fusion. Ubiquitous network access, coupled with an increasingly sophisticated mixture of device-based hardware and software, is enabling context-aware applications at an unprecedented rate. The objective of this chapter is to discuss specific quality attributes with respect to device-side software architectures providing these multimedia and sensor capabilities. This chapter focuses specifically on device-side client architectures rather than network or server architectures. Specific domain requirements and quality attributes are first derived through a synthesis of current research and industry trends, and subsequently analyzed. The analysis reveals some qualitative results that seem unintuitive at first glance but that become more understandable when provided with rationale relative to the handheld domain context.
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Conference papers on the topic "Smartphone Camera Quality"

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Barritt, Nicole, Mohana Kuppuswamy Parthasarathy, Ibrahim Faruq, John Zelek, and Vasudevan Lakshminarayanan. "Fundus camera versus smartphone camera attachment: image quality analysis." In Current Developments in Lens Design and Optical Engineering XX, edited by R. Barry Johnson, Virendra N. Mahajan, and Simon Thibault. SPIE, 2019. http://dx.doi.org/10.1117/12.2528965.

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Ying, Zefeng, Da Pan, and Ping Shi. "Quality Difference Ranking Model For Smartphone Camera Photo Quality Assessment." In 2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 2020. http://dx.doi.org/10.1109/icmew46912.2020.9106040.

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Li, Guoqiang, Bian Yang, and Christoph Busch. "Lightweight Quality Metrics for Smartphone Camera Based Fingerprint Samples." In 2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP). IEEE, 2013. http://dx.doi.org/10.1109/iih-msp.2013.92.

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Zhu, Wenhan, Guangtao Zhai, Zongxi Han, Xiongkuo Min, Tao Wang, Zicheng Zhang, and Xiaokang Yangand. "A Multiple Attributes Image Quality Database for Smartphone Camera Photo Quality Assessment." In 2020 IEEE International Conference on Image Processing (ICIP). IEEE, 2020. http://dx.doi.org/10.1109/icip40778.2020.9191104.

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Zhou, Yuwen, Yunlu Wang, Youyong Kong, and Menghan Hu. "Multi-Indicator Image Quality Assessment of Smartphone Camera Based on Human Subjective Behavior And Perception." In 2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 2020. http://dx.doi.org/10.1109/icmew46912.2020.9105971.

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Yao, Chang, Yuri Lu, Hang Liu, Menghan Hu, and Qingli Li. "Convolutional Neural Networks Based on Residual Block for No-Reference Image Quality Assessment of Smartphone Camera Images." In 2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 2020. http://dx.doi.org/10.1109/icmew46912.2020.9106034.

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Xu, Shuning, Junbing Yan, Menghan Hu, Qingli Li, and Jiantao Zhou. "Quality assessment model for smartphone camera photo based on inception network with residual module and batch normalization." In 2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 2020. http://dx.doi.org/10.1109/icmew46912.2020.9106047.

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Yuan, Zifeng, Yi Qi, Menghan Hu, and Qingli Li. "Opinion-Unaware No-Reference Image Quality Assessment of Smartphone Camera Images Based on Aesthetics and Human Perception." In 2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 2020. http://dx.doi.org/10.1109/icmew46912.2020.9106048.

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Holz, Christian, and Eyal Ofek. "Doubling the Signal Quality of Smartphone Camera Pulse Oximetry Using the Display Screen as a Controllable Selective Light Source." In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018. http://dx.doi.org/10.1109/embc.2018.8513286.

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Truong, Phuong, Alex Phan, Nicolas Williams, and Frank E. Talke. "Development of a Portable Reader for an Optical Intraocular Pressure Sensor." In ASME 2019 28th Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/isps2019-7521.

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Abstract This paper presents various designs of a handheld reader for an interferometric intraocular pressure measurement system. Reflected lights from the implanted sensor form interference fringes which can be captured using a camera. Image processing software was used to analyze the fringe pattern and determine the eye pressure. Various light sources were considered and the LED with a laser line filter was selected for its ability to generate quality fringe patterns and portability. Three generations of handheld readers have been developed and tested. Interference patterns acquired from each reader were compared to assess the limiting and promising features related to measurement time, form factor, working distance, ease of use, and quality of fringes. Results show that the DSLR-based reader has the highest quality images with the largest form factor while the smartphone-based reader offers the smallest form factor with ease of use and accessibility for the patient.
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