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The scale of biological discovery is driven by the vessels in which we can perform assays and analyze results, from multi-well plates to microfluidic compartments. We report on the compatibility of sub-nanoliter single-cell containers or “nanovials” with commercial fluorescence activated cell sorters (FACS). This recent lab on a particle approach utilizes 3D structured microparticles to isolate cells and perform single-cell assays at scale with existing lab equipment. Use of flow cytometry led to detection of fluorescently labeled protein with dynamic ranges spanning 2-3 log and detection limits down to ∼10,000 molecules per nanovial, which was the lowest amount tested. Detection limits were improved compared to fluorescence microscopy measurements using a 20X objective and a cooled CMOS camera. Nanovials with diameters between 35-85 µm could also be sorted with purity from 99-93% on different commercial instruments at throughputs up to 800 events/second. Cell-loaded nanovials were found to have unique forward and side (or back) scatter signatures that enabled gating of cell-containing nanovials using scatter metrics alone. The compatibility of nanovials with widely-available commercial FACS instruments promises to democratize single-cell assays used in discovery of antibodies and cell therapies, by enabling analysis of single cells based on secreted products and leveraging the unmatched analytical capabilities of flow cytometers to sort important clones.

We present the design and experimental characterization of a CMOS sensor based on Single-Photon Avalanche Diodes for direct Time-Of-Flight single-point distance ranging, under high background illumination for short-range applications. The sensing area has a rectangular shape (40 W 10 SPADs) to deal with the backscattered light spot displacement across the detector, dependent on target distance, due to the non-confocal optical setup. Since only few SPADs are illuminated by the laser spot, we implemented a smart laser-spot tracking within the active area, so to define the specific Region-Of-Interest (ROI) with only SPADs hit by signal photons and a smart sharing of the timing electronics, so to significantly improve Signal-to-Noise Ratio (SNR) of TOF measurements and to reduce overall chip area and power consumption. The timing electronics consists of 80 Time-to-Digital Converter (TDC) shared among the 400 SPADs with a self-reconfigurable routing, which dynamically connects the SPADs within the ROI to the available TDCs. The latter have 78 ps resolution and 20 ns Full-Scale Range (FSR), i.e., up to 2 m maximum distance range. An on-chip histogram builder block accumulates TDC conversions so to provide the final TOF histogram. We achieve a precision better than 2.3 mm at 1 m distance and 80% target reflectivity, with 3 klux halogen lamp background illumination and 2 kHz measurement rate. The sensor rejects 10 klux of background light, still with a precision better than 20 mm at 2 m.

Modern image sensor devices regularly aim for low-noise and high frame-rate performances, among other key characteristics. However, not all sensor applications require both low-noise and fast output image acquisition as part of the same sensor. In slow object motion, at low-light illumination levels (such as for night vision), low-noise image performance is necessary but only at a reasonable sensor frame rate. This paper presents a theoretical analysis of the most common pixel readout methods in modern imagers, at two distinct operation modes. One mode is the classical active pixel sensor circuit and the other is a more recent operation mode based on a pulsed biasing scheme introduced for specific application cases, in which the sensor speed is not of much concern. From this perspective, this paper aims to compare the theoretical output thermal noise powers of both kinds of readouts in order to identify which readout method is the read option most suitable for low-light vision without the need to employ advanced and complex techniques to obtain a low-noise imager. In addition to the theoretical results, simulation results are presented as well, as a means to validate the theoretical work.

Neuromorphic engineering, a methodology for emulating synaptic functions or neural systems, has attracted tremendous attention for achieving next-generation artificial intelligence technologies in the field of electronics and photonics. However, to emulate human visual memory, an active pixel sensor array for neuromorphic photonics has yet to be demonstrated, even though it can implement an artificial neuron array in hardware because individual pixels can act as artificial neurons. Here, we present a neuromorphic active pixel image sensor array (NAPISA) chip based on an amorphous oxide semiconductor heterostructure, emulating the human visual memory. In the 8 × 8 NAPISA chip, each pixel with a select transistor and a neuromorphic phototransistor is based on a solution-processed indium zinc oxide back channel layer and sputtered indium gallium zinc oxide front channel layer. These materials are used as a triggering layer for persistent photoconductivity and a high-performance channel layer with outstanding uniformity. The phototransistors in the pixels exhibit both photonic potentiation and depression characteristics by a constant negative and positive gate bias due to charge trapping/detrapping. The visual memory and forgetting behaviors of the NAPISA can be successfully demonstrated by using the pulsed light stencil method without any software or simulation. This study provides valuable information to other neuromorphic devices and systems for next-generation artificial intelligence technologies.

Purpose Demonstrate a novel phantom design using a remote camera imaging method capable of concurrently measuring the position of the x‐ray isocenter and the magnetic resonance imaging (MRI) isocenter on an MR‐linac. Methods A conical frustum with distinct geometric features was machined out of plastic. The phantom was submerged in a small water tank, and aligned using room lasers on a MRIdian MR‐linac (ViewRay Inc., Cleveland, OH). The phantom physical isocenter was visualized in the MR images and related to the DICOM coordinate isocenter. To view the x‐ray isocenter, an intensified CMOS camera system (DoseOptics LLC., Hanover, NH) was placed at the foot of the treatment couch, and centered such that the optical axis of the camera was coincident with the central axis of the treatment bore. Two or four 8.3mm x 24.1cm beams irradiated the phantom from cardinal directions, producing an optical ring on the conical surface of the phantom. The diameter of the ring, measured at the peak intensity, was compared to the known diameter at the position of irradiation to determine the Z‐direction offset of the beam. A star‐shot method was employed on the front face of the frustum to determine X‐Y alignment of the MV beam. Known shifts were applied to the phantom to establish the sensitivity of the method. Results Couch translations, demonstrative of possible isocenter misalignments, on the order of 1mm were detectable for both the radiotherapy and MRI isocenters. Data acquired on the MR‐linac demonstrated an average error of 0.28mm(N=10, R2=0.997, σ=0.37mm) in established Z displacement, and 0.10mm(N=5, σ=0.34mm) in XY directions of the radiotherapy isocenter. Conclusions The phantom was capable of measuring both the MRI and radiotherapy treatment isocenters. This method has the potential to be of use in MR‐linac commissioning, and could be streamlined to be valuable in daily constancy checks of isocenter coincidence.

This article presents a fully integrated multi-modal CMOS cellular sensor/stimulator array chip with 21 952 pixels and 1568-pixel concurrent readouts, while each array pixel can be independently reconfigured to support three sensing and one stimulation modalities: cellular potential recording, optical-point impedance sensing, and bi-phasic current stimulation. The CMOS sensor/stimulator array chip provides 3.6 mm $\times $ 1.6 mm active field-of-view (FoV). Each pixel contains one 8 $\mu \text{m}\,\,\times $ 8 $\mu \text{m}$ gold deposited electrode, one 6 $\mu \text{m}\,\,\times $ 6 $\mu \text{m}$ photodiode, and in-pixel circuits within 8 $\mu \text{m}\,\,\times $ 11 $\mu \text{m}$ pixel area, while the pixel-to-pixel pitch is 16 $\mu \text{m}\,\,\times $ 16 $\mu \text{m}$ . As a proof of concept, the CMOS array is implemented in a standard 130-nm BiCMOS process. Comprehensive electrical testing (potential/optical/four-point impedance/stimulation) and biological measurements (potential/optical/four-point impedance) with on-chip rat cardiomyocytes demonstrate the functionalities and unique advantages of this multi-modality cellular array. With high throughput multi-modal cellular sensing supported at the pixel level, this array chip enables holistic characterization of on-chip cellular samples with single-cell resolution.

Large-area compatible, solar-blind deep-ultraviolet sensors based on active pixels are demonstrated with CMOS amplifiers based on poly-Si thin-film transistors and Ga2 O3 thin-film photoresistors. The active pixel configuration sensor enables approximately 40X higher responsivity compared to a discrete sensor, and the CMOS inverter amplifier exhibits a gain of 210 V/V. The Ga2 O3-based sensors were integrated on the same substrate depositing the films using magnetron sputtering at room temperature, ensuring its compatibility with large-area applications. The responsivity of discrete Ga2 O3 sensors was evaluated at different wavelengths in the deep-ultraviolet and visible ranges, and showed a maximum responsivity of 51 A/W for a wavelength of 232 nm, with a deep-ultraviolet to visible light rejection ratio of approximately 102. The active pixel sensor was implemented as flame detector resulting in an output voltage signal of up to 2 V when the system was exposed to a flame under regular background illumination conditions.

We present a CMOS biochip-based photometer for quantitative immunoassay diagnostics. The photometer quantifies the concentration of antigens based on light absorption, which allows for a low-cost implementation without expensive optical components. We propose a light controller to lower the start-up and settling time of the light source to 30 seconds, to facilitate fast measurement starts, and to decrease the overall measurement times. The application-specific integrated circuit (ASIC) contains a 6 x 7-sensor array with 100 $\boldsymbol{\mu }$ m x 100 $\boldsymbol{\mu }$ m photodiodes that serve as signal transducers. The ASIC was developed in a normal 0.35- $\boldsymbol{\mu }$ m CMOS technology, avoiding the need for expensive post-CMOS processes. We present our strategy for the assembly of the ASIC and the immobilization of antibodies. For its first time, we demonstrate the quantification of prostate specific antigen (PSA) with an optoelectronic CMOS biochip using this approach. A PSA immunoassay is performed on the top surface of the CMOS sensor array, enzyme kinetics and PSA concentration are measured within 6 minutes with a limit of detection (LoD) of 0.5 ng/ml, which meets clinical testing requirements. We achieve an overall coefficient of variation (CV) of 7%, which is good compared to other point-of-care (PoC) systems.

Comparing with the application of charge coupled device (CCD) sensor, a kind of interference stripe noise (ISN) can be observed easily from the complementary metal-oxide-semiconductor (CMOS) sensor-based digital holographic measurement (DHM) system because a series of optic coatings and filters are used in front of that sensor in order to improve its imaging effect. The improper assembly or the micro manufacturing error of these optic components may create the unexpected interference phenomena in the imaging sensor. To reduce that noise, an effective image processing method is developed. On one hand the Laplacian pyramid method is used to highlight the ISN and a cartoon-texture decomposition technique is carried out to remove the additive ISN. On the other hand, an improved Lee filtering is performed to restrain the multiplicative ISN. Extensive experiment results have shown that the image quality can be improved after the ISN reduction and this method is fit for solving a deionized water temperature estimation application where the texture complexity of target image is relatively low.

In this work, we demonstrate a novel one-transistor active pixel sensor (1T-APS) with tunable sensitivity using 22 nm FD-SOI technology. With various pixel length ( $\text{L}_{P}$ ) and active region length ( $\text{L}_{A}$ ), extra control gates are introduced to modulate the effective $\text{L}_{A}$ and the photoelectron distribution under the buried oxide layer/substrate interface. With the shorter effective $\text{L}_{A}$ , the higher photoelectron concentration is revealed, leading to the higher sensitivity. A sensitivity increase up to 42.28% is obtained with the largest $\text{L}_{P}/\text{L}_{A}$ ratio. The tunable sensitivity and extremely compact structure make the device very promising for high-dynamic-range imaging applications with a higher resolution and a larger fill factor.

A hardware–software complex that has no analogues in Russia and abroad and that is designed to measure the distribution of the cutoff frequency of electroluminescence over the area of a light-emitting heterostructure (LHS) is described. The complex provides a spatial resolution of 0.65 µm, an upper measurement limit of 40 MHz, and a relative error of 2%. The electroluminescence cutoff frequency in local areas of an LHS is determined from the decay of the brightness of pixels of LHS images by 1.19 times obtained using a digital CMOS camera with a step-by-step increase in the pulse repetition rate of the LHS-supplying current with an off-duty factor of 2. The complex and the measurement method were tested on commercial green light-emitting diodes. The results of measuring the cutoff-frequency distribution can be used to assess the homogeneity of LHSs.

In this study, we report the design and simulation of an electrostatic ion lens system consisting of 22 round metal plates. The opening of the extractor plate is covered with metal mesh, which is for shielding the interaction region of the lens system from the high DC voltages applied to all other plates than the repeller and extractor plates. The Simion simulation shows that both velocity-mapping and time focusing can be achieved simultaneously when appropriate voltages are applied to each of the plates. This makes the ion lens system be able to focus large ionic volumes in all three dimensions, which is an essential requirement for crossed ion-molecule scattering studies. A three-dimensional ion velocity measurement system with multi-hit and potential multi-mass capability is built, which consists of a microchannel plate (MCP), a P47 phosphor screen, a CMOS camera, a fast photomultiplier tube (PMT), and a high-speed digitizer. The two velocity components perpendicular to the flight axis are measured by the CMOS camera, and the time-of-flight, from which the velocity component along the flight axis can be deduced, is measured by the PMT. A Labview program is written to combine the two measurements for building the full three-dimensional ion velocity in real time on a frame-by-frame basis. The multi-hit capability comes from the fact that multiple ions from the camera and PMT in the same frame can be correlated with each other based on their various intensities. We demonstrate this by using the photodissociation of CH3I at 304 nm.

Objective A mobile handheld snapshot hyperspectral imaging device was developed and tested for in vivo skin evaluation using a new spectral imaging technology. Methods The device is equipped with four different LED light sources (VIS, 810 nm, 850 nm, and 940 nm) for illumination. Based on a diffractive optical element (DOE) combined with a CMOS sensor chip, a snapshot hyperspectral imager is achieved for the application on human skin. The diffractive optical element (DOE) consists of a two‐dimensional array of identically repeated diffractive microstructures. One hyperspectral image for all wavelength regions is taken within a few seconds. Complex recalculation of the VIS spectral distribution and image information from the received DOE image requires several minutes, depending on computing performance. A risk assessment on the irradiation sources shows no risk of harm due to the LED radiation. Results Skin tone color patches experiments reproducibly deliver images and spectra of different skin tones. First in vivo use of the device identified pigmentation changes within the field of view. Conclusion We present a working mobile snapshot hyperspectral imaging tool based on diffractive optical elements. This device or future developments thereof can be used for broad skin evaluation in vivo.

In this work, a study case is presented in which the design of the layout for a CMOS sensor cell is partially automated by implementing a metaheuristic algorithm to find the best tradeoff between two conflicting objectives (two quantitative opposite and not totally independent yet desired performance or design qualities) among the set of feasible layout and electronic device configurations within a constricted search space. The feasibility of a solution (a particular configuration) and its capability to fulfill every requested objective, is determined by its compliance to the CMOS-MEMS design rules and fabrication process. Any given solution besides showing optimal or very near-to-the-optimal characteristics, must be suitable to be fabricated in the CMOS conventional process which for this case is a $$0.5\,\mu \hbox {m}$$ , 3-metal 2-poly N-well fabrication, beside this, since monolithic inertial sensors generally contains embedded movable electromechanical parts a surface micromachining must be considered. Simulation data and behavior of the bio-inspired metaheuristic algorithm used during the design process are presented, as well as electromechanical simulation results based the automatic-generated solutions.

Due to the delay in the row-wise exposure and the lack of stable support when a photographer holds a CMOS camera, video jitter and rolling shutter distortion are closely coupled degradations in the captured videos. However, previous methods have rarely considered both phenomena and usually treat them separately, with stabilization approaches that are unable to handle the rolling shutter effect and rolling shutter removal algorithms that are incapable of addressing motion shake. To tackle this problem, we propose a novel method that simultaneously stabilizes and rectifies a rolling shutter shaky video. The key issue is to estimate both inter-frame motion and intra-frame motion. Specifically, for each pair of adjacent frames, we first estimate a set of spatially variant inter-frame motions using a neighbor-motion-aware local motion model, where the classical mesh-based model is improved by introducing a new constraint to enhance the neighbor motion consistency. Then, different from other 2D rolling shutter removal methods that assume the pixels in the same row have a single intra-frame motion, we build a novel mesh-based intra-frame motion calculation model to cope with the depth variation in a mesh row and obtain more faithful estimation results. Finally, temporal and spatial motion constraints and an adaptive weight assignment strategy are considered together to generate the optimal warping transformations for different motion situations. Experimental results demonstrate the effectiveness and superiority of the proposed method when compared with other state-of-the-art methods.

This work presents a low noise active pixel sensor. It uses one additional transistor compared to standard 4T pixel to obtain 1/f noise reduction and high conversion gain. 1/f noise is reduced by periodically switching the in-pixel source follower between depletion and inversion. The depletion state is achieved by re-configuring the source follower into a MOS capacitor and depleting the channel by controlling the source-drain terminal. The state change of the in-pixel source follower also enhances the conversion gain. The test chip has a $64 \times 64$ pixel array with a $10~ {\mu }\text{m}$ pixel pitch fabricated in 350 nm AMS process. The measured integrated noise of a pixel in the frequency band 128 Hz to 50 KHz is $728~ {\mu V_{rms}}$ without switching. At a switching frequency of 4 MHz, the integrated noise reduces to $306~ {\mu V_{rms}}$ after switching resulting in a 7.5 dB reduction. The input referred noise is reduced from $26 {e_{rms}^{-}}$ to $7.3 {e_{rms}^{-}}$ after applying switching. When both, switching and conversion gain enhancement are applied, the input referred noise is further reduced to $2.3 {e_{rms}^{-}}$ with an enhanced conversion gain of $398\,\, {\mu V/e^{-}}$ .

During the past few decades, there has been a growing trend towards the use of smartphone-based analysis systems. This is mainly due to its ubiquity, its increasing computing capacity, its relatively low cost and the ability to acquire and process data at the same time. Furthermore, there are many sensors integrated into a smartphone, for example a complementary metal-oxide semiconductor (CMOS) sensor. A CMOS sensor enables optical analysis for example by using it as a colorimeter, photometer or spectrometer. This review explores the current state-of-the-art smartphone-based optical analysis systems in various areas of application. It is organized into three sections, each of which investigates one class of smartphone-based devices: (i) smartphone-based colorimeters (ii) smartphone-based photo- and spectrometers and (iii) smartphone-based fluorimeters.

This paper is representing an idea on the use of the quadcopter for the sake of the pivotal issues like defense tasks or climate calamities/changes which threaten the world to plunge into hazards. So, we need efficient ways to identify areas of potential hazard risks and monitor them closely in an easier manner. Due to these hazardous and risky challenges it is not always optimal for humans to take up this task rather use a quadcopter for the search and rescue operation to save the lives of the people from risks. The base idea for our drone is to use a DJI NAZA-M Lite Flight controller with GPS antenna, a low latency camera with a 0.33-inch CMOS sensor with a 1.2 mm wide angle (150degree) lens and a transmitter with 2.4 GHz bandwidth makes it suitable at the time of search and rescue. By using an arduino and an MPU6050 sensor, we can map its gyro and accelerometer values to the control sticks of the quadcopter. We have also added a small 5 V speaker along with a couple of other sensors like temperature, rain/humidity sensor, gas sensors etc. The use of these components along with gesture control features can be used at the time of surveillance by defense or at the time of natural calamities for the search and rescue operations making it advantageous to use by any sort of person in these risky situations.

This paper presents a comparative study of six active pixel sensor (APS) schemes by means of simulations and experiments. The optical sensor used was a silicon photodiode with integrated electronics in a standard 0.35 µm CMOS technology. We analyzed how the transistor characteristics, such as channel resistance and leakage current, among others, can influence the APS response. Furthermore, we demonstrated how the choice of APS model affects sensor parameters such as output swing and fill factor, among others. The results presented and the understanding of the operational cycle of the CMOS transfer-gated APS aims at guiding better choices for different applications and the better transistor type in the project.

A markerless computer aided orthopaedic platform will require a complex computer vision system to isolate and track rigid bodies used to localize a robot to a patient. Isolating rigid bodies such as bone requires accurate segmentation and this study explores using diffuse laser reflectivity to accurately classify tissue. Lasers (red at 650nm and infrared – IR – at 850nm) intersected four material types; cartilage, ligament, muscle and metal surgical tools within a controlled cadaveric setup. Images were captured with an infrared CMOS sensor, pre-processed to isolate laser centers, and resized to test information requirements. Images for both laser types were scaled from $5\times5$ pixels to $30\times30$ pixels and trained on a convolutional neural network, GoogLeNet. At sizes above $15\times15$ pixels, the IR laser had a higher classification accuracy, reaching 97.8% at $30\times30$ pixels, whereas the red laser peaked at 94.1%. It was shown as not possible to qualitatively identify materials that were not trained in the network based on their probability outputs. Further work will be performed to classify multiple points in a single scene as a step toward segmenting entire surgical views for markerless Computer Assisted Orthopedic Surgery (CAOS) systems.

In this study a specially revised version of the concept for measuring the angle-of-arrival (AOA) of incidence light was used, which is particularly well suited for the construction of trigonometric sensor concepts with external dimensions of only a few millimeters. The aim of the study was to break down the interrelationships for the overall systemically achievable accuracies. The study therefore focused on the lowest possible power consumption of the LED light source used, minimum component dimensions and quantities, outline of the practicable minimum distances between LED light source and integrated sensor unit, robustness of the sensor against gradients and intensity changes in lighting, illumination intensity and sensor noise, as well as the requirements for the precision of the mechanical components used. It could be shown that the key limiting factor isn't the optical/electronic precision of the CMOS sensor concept used, but the finite precision of the mechanical components.

Singapore’s first multi-source high-flux solar simulator (HFSS) that comprises an array of seven 4-kWe xenon short-arc lamps close-coupled with ellipsoidal reflectors is designed, constructed, and characterized. An indirect mapping system that consists of a water-cooled Lambertian target, a CMOS camera, and a heat-flux gauge is adopted herein to experimentally characterize the performance of the developed HFSS. A calibration constant of 192.8 ± 9.6 kW m−2 (GS µs−1)–1 is determined and used to transform the raw-flux maps with grayscale values to the absolute-flux maps. Utilizing a series of flexible and precise adjusters, the variability of ± 1 mm in the x- and y-directions of the peak flux points of the radiation modules is measured. A peak flux of 7740 kW m−2 is measured for the sum of all 7 radiation modules. Average radiative fluxes of 4191 kW m−2 and 2933 kW m−2 can be observed from circular target areas of O40 mm and O60 mm, respectively, associated with promising electricity-to-target transfer efficiencies of 18.8% and 29.6%. A Monte Carlo ray-tracing (MCRT) model is calibrated by the experimental data. Based on the minimum root-mean-standard deviation between the measured and simulated results of the radiative power on the target, the optimal parameters of the MCRT model include the arc radius of 3.4 mm and the reflector surface error of 1.1 mrad.

Purpose The smart image sensor (SIS) which integrated with both sensor and smart processor has been widely applied in vision-based intelligent perception. In these applications, the linearity of the image sensor is crucial for better processing performance. However, the simple source-follower based readout circuit in the conventional SIS introduces significant nonlinearity. This paper aims to design a low-power in-pixel buffer circuit applied in the high-linearity SIS for the smart perception applications. Design/methodology/approach The linearity of the SIS is improved by eliminating the non-ideal effects of transistors and cancelling dynamic threshold voltage that changes with the process variation, voltage and temperature. A low parasitic capacitance low leakage switch is proposed to further improve the linearity of the buffer. Moreover, an area-efficient SIS architecture with a sharing mechanism is presented to further reduce the number of in-pixel transistors. Findings A low parasitic capacitance low leakage switch and a gate-source voltage pre-storage method are proposed to further improve the linearity of the buffer. Nonlinear effects introduced by parasitic capacitance switching leakage, etc., have been investigated and solved by proposing low-parasitic and low-leakage switches. The linearity is improved without a power-hungry operational amplifier-based calibration circuit and a noticeable power consumption increment. Originality/value The proposed design is implemented using a standard 0.18-µm CMOS process with the active area of 102 µm2. At the power consumption of 5.6 µW, the measured linearity is −63 dB, which is nearly 27 dB better than conventional active pixel sensor (APS) implementation. The proposed low-power buffer circuit increase not only the performance of the SIS but also the lifetime of the smart perception system.

We propose a novel spectroscopic ellipsometry capable of measuring line profile of the film thicknesses with a single image at once. By adopting a polarization-pixelated CMOS camera and an imaging spectrometer, spatial, spectral and polarization information of the film structure can be acquired at the frame rate of the camera without any mechanical or electrical adjustments of polarizing optical components. The proposed system is beneficial not only to provide film thickness of the specimen with a single image acquisition, but also to analyze the spatial features of the film layers.

A robust multichannel smartphone spectrometer exploiting multiorder diffraction imaging on a smartphone camera is reported. The instrument utilizes a thin film diffractive element generating multiple orders of diffracted light from a broadband visible source (white LED, λ = 400-700 nm). The smartphone's CMOS camera captures all the diffraction orders simultaneously, producing a 2-D image. Each of these diffraction orders can be utilized as a single optical channel for dedicated samples enabling simultaneous multiple sample analysis. The wavelength distribution along the diffraction direction produces a tunable spectral resolution of δλ ~1.6 to 3.0 nm/pixel over the bandwidth of Δλ = 300 nm. A customized app processes each diffraction image into spectra. 3-D printing is used to create the entire instrument prototype. As an initial demonstration, simultaneous absorption measurements of reference and sample cells using the first diffraction orders (m = +1 and -1) is shown. Absorption spectra for a laser dye (Rhodamine B) and a pH-responsive buffer (bromothymol blue) are measured. This offers a low cost (

A conventional large-area indirect-conversion X-ray detector usually adopts front side illumination (FSI) of a scintillator atop a photodiode-integrated thin-film transistor (TFT) array. This work however proposes a backside illuminated (BSI) three-dimensional dual-gate photosensitive a-Si:H TFT (3-D DGTFT) on a scintillating glass substrate, aiming for indirect-conversion X-ray detection. It not only improves the sensitivity with a 3-D photosensitive TFT as an active pixel sensor, but also enhances the resolution and photon utilization by reducing photon scattering and optical crosstalk. Backside illumination of 3-D photosensitive TFT-integrated scintillating glass therefore provides an alternative approach to large-area indirect-conversion X-ray imaging.

This article reports on a highly-sensitive indirect-conversion X-ray detector with an embedded photodiode formed by a scintillator-coupled 3-D photosensitive thin-film transistor. A high X-ray sensitivity up to 2.5 × 105 μC·Gy−1·cm−2 at a dose of 1 mGy is achieved due to full photon utilization and a high photo gain of ∼104 by operating it in an active pixel sensor format. These performance characteristics make it a great promise for low-dose and high-spatial resolution large-area indirect-conversion X-ray detection.

In this paper, a low-power readout using reconfigurable cyclic ADC for CMOS image sensors is proposed. It reduces the total number of pixels to be read by taking advantage of pixel correlation. The required number of ADC operations is reduced, resulting in power saving. In contrast to the existing pixel correlation-based approaches, which focus only on the intensity differences, in the proposed method, the polarity of the differences is also taken into account. It helps in preserving fine edges representing features such as texture. The discarded or unread pixels are interpolated on-chip while reconfiguring the ADC input range according to the interpolation step size. Furthermore, this reduces the number of ADC conversion cycles by 25% to 50% for interpolation steps of 16 LSB and 64 LSBs, respectively. The ADC is designed and fabricated in UMC 180-nm CMOS technology, and the proposed method is verified for standard test images. The reconstructed images incorporating ADC non-linearities result in average Pratt’s FoM values of 0.88, 0.86, and 0.81 for 60%, 70%, and 74% compression, respectively. The corresponding best values achieved by the existing approaches are 0.86, 0.80, and 0.77, respectively. The improvement in FoM is observed due to the consideration of polarity information. The proposed technique results from 33% to 50% power saving for 80% compression in $512\times512$ image, using reconfigurable ADC. Therefore, it is suitable for a power efficient CMOS sensor design.

We demonstrate a versatile thin lensless camera with a designed phase-mask placed at sub-2 mm from an imaging CMOS sensor. Using wave optics and phase retrieval methods, we present a general-purpose framework to create phase-masks that achieve desired sharp point-spread-functions (PSFs) for desired camera thicknesses. From a single 2D encoded measurement, we show the reconstruction of high-resolution 2D images, computational refocusing, and 3D imaging. This ability is made possible by our proposed high-performance contour-based PSF. The heuristic contour-based PSF is designed using concepts in signal processing to achieve maximal information transfer to a bit-depth limited sensor. Due to the efficient coding, we can use fast linear methods for high-quality image reconstructions and switch to iterative nonlinear methods for higher fidelity reconstructions and 3D imaging.

This manuscript introduces a handheld machine vision based system design that is capable of standalone operation using touch screen based user interface and also can operate through smartphone based android app. System uses 8.0 Megapixel, 1080p CMOS camera interfaced with quad-core ARM Cortex-A53 processor based computing platform (Raspberry Pi computing platform) for real time image acquisition and processing. Multi-spectral led array has been used to compensate the effect of external illumination and also to increase the accuracy of measurement. System stores acquired images on interfaced 16.0 G.B. external memory card with date and time information. Various segmentation methods have been explored to extract region of interest in acquired images and compared based on the capability of segmentation in real-time. Segmented images have been used to extract different features such as color, shape, size and texture using various image processing algorithms. Extracted features have been fused together and undergone through different statistical and neural network based modelling methods to correlate features dataset generated using handheld system with standard quality parameters of collected citrus samples. Performance of the established correlation models for various quality parameters such as chlorophyll, sugar content, TSS, weight, pH and volume have been evaluated and best performed models for each quality parameter has been used to train the developed handheld machine vision based system. Overall system is battery operated and also enables cloud connectivity using on-board Wi-Fi facility or smartphone based android app. Overall device has dimensions of 12.0 × 6.0 × 4.0 (in cm), weighs 139.07 g and runs with 5-V rechargeable battery.

The electrostatic distribution of an electron bombarded CMOS (EBCMOS) was simulated by Ansoft Maxwell 3D software. Specifically, we studied how the electrostatic distribution was affected by the structure of a back-side bombarded CMOS (BSB-CMOS) and the anode position in electron-bombarded sensors. The simulation results reveal that the electrostatic field may cause a fault in the signal readout of the BSB-CMOS when the anode is positioned under the BSB-CMOS. In contrast, we found that the structure of an EBCMOS will aid electron focusing when the anode is positioned above the BSB-CMOS and the doping concentration of the electron multiplier layer is high. However, the high doping concentration of the electron multiplier layer will reduce the electron collection efficiency due to its rapid electron-hole recombination. We then designed a structure in which the multiplier layer has an overlying ultra-thin highly-doped layer, with an electrostatic distribution that functions to focus electrons. At the same time, this configuration can effectively prevent most of the multiplier electrons from recombining because ultra-thin highly-doped layer is much thinner than incident depth for the high-energy electron. This simulation study will provide a theoretical foundation for the fabrication of high-performance EBCMOS devices. Graphic abstract: a) EBCMOS physical model in Ansoft Maxwell 3D; b) The distribution of electrostatic distribution for BSB-CMOS with an ultra-thin heavily-doped layer. Electrostatic distribution of EBCMOS with different configurations were simulated. The results reveal that the electrostatic field may cause an erroneous readout of the BSB-CMOS if the anode is positioned under the BSB-CMOS. If the high voltage anode is positioned above the CMOS sensor, this is improved, especially when an ultrathin highly-doped multiplier layer is added to improve electron collection efficiency. This study provides a theoretical foundation for the fabrication of high performance EBCMOS devices.

The glass capillary plate (CP) gas detector is a hole-type micropattern gas detector (MPGD) as well as a gas electron multiplier (GEM). An interesting feature of the hole-type MPGD is that since the electron multiplication takes place in each of the highly granulated holes, pixelized 2-D imaging with a high position resolution is possible. Using the CP, we have been developing a gas scintillation imager (GSI) for digital X-ray radiography, cosmic X-ray polarimetry, and neutron imaging. To realize the 2-D imaging capability, we exploit the visible and near-infrared (NIR) scintillation photons emitted from each hole upon gas excitation. This emission occurs simultaneously with electron multiplication. The readout of the scintillation photons has been carried out using an image-intensified charge-coupled device (CCD) or CMOS camera, or a cooled low-noise CCD/CMOS camera, coupled to an optical mirror or lens systems. In this article, we review the properties of the GSI as X-ray and neutron imagers and describe the outlook for future developments.

Recent developments in IC technology rely on device scaling and 3-D integration, resulting in billions of devices compacted into a small area. These trends degrade the lifetime and reliability of the system due to an increase in temperature caused by high power densities. Dynamically managing a system based on the thermal characteristics is important to mitigate this issue. An on-chip thermal-aware system composed of hundreds of distributed thermal sensors is proposed. A hybrid spintronic/CMOS-based thermal sensor is described that exploits the thermal response and small area of an antiparallel magnetic tunnel junction. The sensor cell consumes as little as 500 pJ to read 1024 thermal sensor nodes and generates a thermal map of a system composed of $32 \times 32$ thermal sensors. The sensor cell exhibits a thermal linearity ( $R^{2}$ ) up to 0.983 and a thermal sensitivity of 1.91 mV/K over the commercial temperature range of 0 °C to 85 °C while consuming $32~\mu \text{W}$ .

The spatial resolution and the reconstruction efficiency of the main drift chamber of the Beijing Spectrometer III has degraded after more than nine years of operation. An improved new inner drift chamber has been constructed to replace the old chamber in case of the radiation damage. A monolithic active pixel sensor (MAPS) based detector prototype is selected as one of the prototype schemes for the inner chamber upgrade. Design a set of MAPS readout electronics system for the inner drift chamber upgrade. This system can verify the function and performance of the selected MAPS chip and discover the matters needing attention when designing large-scale detectors. The electronics system design is composed of three parts. The first part is flexible printed circuit boards (PCBs) assembled with the MAPS chips. The second part is digital readout boards, which are connected to the flexible PCBs via FPGA mezzanine card cables. The digital readout board realizes the configuration of the MAPS chip register, receives and processes the data output by the MAPS chip, and transfers the processed data to the DAQ device. The third part includes a readout control board and two fan-out boards that used to separately fan out the trigger signal and the start signal to all the digital readout boards. A MAPS readout electronics system consisting of five MAPS based detector prototypes is designed. The system can work stably under the electron beam experimental conditions with a frequency up to 2 kHz and energy ranging from 1 to 5 GeV. The system detection efficiency of the electron beam is $$\sim 95\%$$, and the spatial resolution is $$\sim 5.3\, \upmu \hbox {m}$$ at electron energies of 1 GeV. The design of the electronics system meets the requirements for verifying the performance of the MAPS chips and the technical feasibility of the detector structure.

In order to better solve the problem of automatic identification of quality control line and detection line in the detection of gold standard test strip, this paper proposes to collect the image information of gold standard test strip after color rendering through CMOS sensor, preprocess the obtained information, transform RGB image into gray image, build cloud model in the CIELAB/HSV/HSL space, and apply the improved AdaBoost algorithm to determine the position of detection line and quality control line Place. Compared with the traditional template matching method, it improves the accuracy and accuracy of recognition.

A CMOS sensor chip was used, together with an Arduino microcontroller, to create and verify a low-power low-cost optical motion detector for use in traffic detection under dark and daylight conditions. The chip can sense object features with very high dynamic range. On-chip near sensor image processing was used to reduce the data to be transferred to a host computer. A method using local extrema point detection was used to estimate motion through time-to-impact (TTI). Sensor data from the headlights of an approaching/passing car were used to extract TTI values similar to estimations from distance and speed of the object. The method can be used for detection of approaching objects to switch on streetlights (dark conditions) or sensors for traffic lights instead of magnetic sensors in the streets or conventional cameras (dark and daylight conditions). A sensor with a microcontroller operating at low clock frequency will consume less than 30 mW in this application.

Large-scale microelectrode arrays offers enhanced spatiotemporal resolution in electrophysiology studies.. In this paper, we discuss the design and performance of an electrochemical detector array which is capable of 1024-ch parallel cyclic voltammetry (CV) as well as other electrochemical measurements. The electrochemical detector is fabricated using a custom-designed CMOS chip which integrates both the circuity and on-chip microelectrode array, to operate and record from electrochemical measurements. For parallel 1024-ch recordings, 1024 capacitor-based integrating transimpedance amplifiers (TIA) are designed and integrated. The TIA design features the bipolar capabilities for measuring both negative and positive electrochemical currents due to reduction and oxidation of molecules. The resulted dynamic range of this TIA is −700 pA – 1968 pA. CV can be used to examine the quality of electrochemical electrodes by measuring the double-layer capacitance. Double-layer capacitance forms at the electrode-electrolyte interface and is a function of the effective area of the electrode. Thus, a contaminated electrode can have smaller effective area resulting in smaller double-layer capacitance. Using the parallel CV capability of the monolithic CMOS device, the double layer capacitance of all 1024 electrodes are simultaneously measured to examine the status of the electrodes’ surface in real time. The initial measurement of the electrode array showed a mean capacitance of 466 pF. After plasma treatment to remove contamination on the electrode’s surface, the increased capacitance was 1.36nF nearly tripling the effective surface area. We have successfully developed of 1024-ch electrochemical detector array using the monolithic CMOS sensor. The CV functionality was validated by measuring the double-layer capacitance of the on-chip electrode array. This method can accelerate the characterization of a massive electrode array before analytical experiments to provide well-controlled electrochemical electrodes, which is crucial in conducting reliable electrochemical measurements.

Over the last half century, photography has evolved from photochemical reactions induced on a photosensitive film to optoelectronic devices employed in digital image. Video has done the same migration from classical film movies to optoelectronic acquisition and storage. Digital and video cameras share optics with traditional film cameras, but the image recording is realized by an optoelectronic device –a CCD or CMOS sensor– rather than a film. The quantity of digital photo and video images has dramatically increased in the last decade, arising from the ubiquitous cameras of mobile phones. Despite their popularity, condensed tutorial articles on the subject are still scarce. This work intends to contribute to the knowledge of this field with a medium-level short course that is currently being taughtin a broader subject (Consumer Photonics) to undergraduate students of Telecommunication Engineers at the Universidad Politecnica de Madrid. The course can be followed by students having a basic background on Physics and specifically on Optics and Semiconductors. The course is divided into two chapters. An introduction to optics of cameras and basic concepts of photography has been considered necessary to follow the second part, which is entirely devoted to optoelectronic sensors

Frame-based optical flow (OF) methods struggle in the presence of large motion and occlusion due to slow frame rates. Optical flow of dynamic vision sensor (DVS) has gained attention recently as a way to overcome these shortcomings. DVS reports “events” corresponding log intensity changes exceeding a specific threshold, with an accuracy of microsecond order. The increased temporal sampling rate are indeed helpful, but the poor spatial fidelity of DVS outputs make events-based OF less reliable overall. In this work, we consider a new sensor called DAViS that combines the conventional active pixel sensor (APS) and DVS circuitries, yielding a conventional intensity image frames as well as the events. We propose a novel optical flow method designed specifically for a DAViS camera that leverages the high spatial fidelity of intensity image frames and the high temporal resolution of events generated by DVS. Hence, the proposed DAViS-OF method yields reliable motion vector estimates while overcoming the fast motion and occlusion problems. The proposed DAViS-OF method is computationally efficient and is suitable for real-time implementation.

Several recent studies on compressive video sensing realized scene capture beyond the fundamental trade-off limit between spatial resolution and temporal resolution using random space-time sampling. However, most of these studies obtained results for higher-frame-rate video that was produced in simulation experiments or using an optically simulated random sampling camera, because there are currently no commercially available image sensors with random exposure or sampling capabilities. We fabricated a prototype complementary metal-oxide-semiconductor (CMOS) image sensor with quasi pixel-wise exposure timing that can realize nonuniform space-time sampling. The prototype sensor resets exposures independently by columns and fixes these exposures by rows for each 8 × 8-pixel block. This CMOS sensor is not fully controllable the pixels and has line-dependent control, but offers greater flexibility when compared with regular CMOS or charge-coupled device sensors with global or rolling shutters. We propose a method of realizing pseudo-random sampling for high-speed video acquisition that uses the flexibility of the CMOS sensor. We reconstruct the high-speed video sequence from images produced in pseudo-random sampling using a pre-learned decoder.

Sorting and quality inspection of fruits is still a time-consuming task because of the low level of automation. Natural products exhibit a greater variance compared to manufactured products regarding quality and dimensions, which complicates their automated processing. In our paper, we propose a method to determine the orientation of fruits by applying a specially trained Convolutional Neural Network to 2.5-dimensional image data generated by a combination of a color CMOS camera and a red line laser. We achieve an accuracy of the orientation prediction of approximately 5 degrees, which presents very promising results for the automation of fruit packing systems.