scholarly journals CMOS Image Sensor Dreams of Intelligent Sensors. Image Sensors with Analog Image Processing Function.

1999 ◽  
Vol 53 (2) ◽  
pp. 166-171
Author(s):  
Shoji Kawahito ◽  
Kiyoharu Aizawa
Keyword(s):  
Image Processing ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Image Sensors ◽  
Intelligent Sensors ◽  
Processing Function ◽  
Analog Image Processing

scholarly journals Automatic Range Adjustment of the Fluorescence Immunochromatographic Assay Based on Image Processing

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 209 ◽  
Author(s):  
Ruixin Jiang ◽  
Huihuang Wu ◽  
Jianpeng Yang ◽  
Haiyan Jiang ◽  
Min Du ◽  
...  
Keyword(s):  
Image Processing ◽  
Point Of Care ◽  
Strong Stability ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Image Sensors ◽  
Oxide Semiconductor ◽  
Detection Sensitivity ◽  
Immunochromatographic Assay ◽  
Detection Range

As an emerging technology, fluorescence immunochromatographic assay (FICA) has the advantages of high sensitivity, strong stability and specificity, which is widely used in the fields of medical testing, food safety and environmental monitoring. The FICA reader based on image processing meets the needs of point-of-care testing because of its simple operation, portability and fast detection speed. However, the image gray level of common image sensors limits the detection range of the FICA reader, and high-precision image sensors are expensive, which is not conducive to the popularization of the instrument. In this paper, FICA strips’ image was collected using a common complementary metal oxide semiconductor (CMOS) image sensor and a range adjustment mechanism was established to automatically adjust the exposure time of the CMOS image sensor to achieve the effect of range expansion. The detection sensitivity showed a onefold increase, and the upper detection limit showed a twofold increase after the proposed method was implemented. In addition, in the experiments of linearity and accuracy, the fitting degree (R2) of the fitted curves both reached 0.999. Therefore, the automatic range adjustment method can obviously improve the detection range of the FICA reader based on image processing.

A Wearable Supporting System for Visually Impaired People in Operating Capacitive Touchscreen

2011 ◽  
Vol 103 ◽  
pp. 687-694
Author(s):  
Akira Yamawaki ◽  
Serikawa Seiichi
Keyword(s):  
Image Processing ◽  
Visually Impaired ◽  
High Performance ◽  
Middle Finger ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Supporting System ◽  
Visually Impaired People ◽  
Impaired People ◽  
Natural Way

We propose a wearable supporting system with a CMOS image sensor for the visually impaired people in operating capacitive touchscreen. This system attaches the CMOS image sensor without a lens to the tip of the middle finger. The icons and buttons displayed on the touchscreen are replaced to the color barcodes. Touching the surface of the touchscreen with the CMOS image sensor directly, the color barcode is detected and decoded. The decoded results are returned to the user by some interaction like audio. Then, the user touches the button area around the color barcode by the forefinger to operate the target device. This system can provide very easy and natural way for operating the touchscreen to the visually impaired people who usually recognize the materials by the finger. Any mechanical modification of the target device is not needed. The modification can be made by changing its software program. Since the color barcode is sensed by the image sensor without any lens touching the surface of the touchscreen, each bar in the color barcode should be blurred. So, we　develop an easy and simple image processing to handle such problem. We design it as the hardware module to achieve the high performance and low-power wearable device. A prototype hardware using an FPGA shows the hardware size, the performance and the actual demonstration.

scholarly journals A CMOS voltage-mode image sensing system

2021 ◽  
Author(s):  
Jun Long Zhang
Keyword(s):  
Cmos Image Sensor ◽  
Cmos Technology ◽  
Image Sensor ◽  
Electrical Signal ◽  
Image Sensors ◽  
Analog To Digital ◽  
Light Sensing ◽  
Image Sensing ◽  
Cmos Image Sensors ◽  
Pixel Sensors

A CMOS image sensor consists of a light sensing region that converts photonic energy to an electrical signal and a peripheral circuitry that performs signal conditioning and post-processing. This project investgates the principle and design of CMOS active image sensors. The basic concepts and principle of CMOS image sensors are investigated. The advantages of CMOS image sensors over charge-coupled device (CCD) image sensors are presented. Both passive pixel sensors (PPS) and acive pixel sensors (APS) are examined in detail. The noise of CMOS image sensors is investigated and correlated double sampling (CDS) techniques are examined. The design of APS arrays, CDS circuits and 8-bit analog to-digital converters in TSMC-0.18μm 1.8V CMOS technology is presented. The simulation results and layout of the designed CMOS image sensor are presented.

PureView Technology (Optimisation & Evaluation Techniques in Image Processing)

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Jyoti Prakash Patra ◽  
Puru Agrawal
Keyword(s):  
Image Processing ◽  
High Resolution ◽  
High Performance ◽  
Image Sensor ◽  
Image Sensors ◽  
Resolution Image ◽  
High Resolution Image ◽  
Lighting Conditions ◽  
High Quality Image ◽  
Evaluation Techniques

PureView Technology is the combination of a super high-resolution image sensor and high-performance optics. It further applies advanced image processing algorithms and pixel oversampling to give the best quality outputs. It uses pixel oversampling method. Pixel oversampling combines many pixels to create a single (super) pixel. When this happens, we keep virtually all the details but filter away visual noise from the image. The speckled, grainy look we tend to get in low-lighting conditions is greatly reduced. One of the major benefits of this technology is loss-less zoom. The level of pixel oversampling is highest when we are not using the zoom. It gradually decreases until we hit maximum zoom, where there is no oversampling. This technique thus allows us to have loss-less zooms even when we are using the camera for taking zoomed in photos. The core of this technology lies somewhere in the satellite imagery system which uses a similar method of pixel oversampling and high-resolution image sensors. With PureView, uses a system called oversampling, which takes the original greater number of megapixels captured with the enormous sensor and reduces them to a high-quality image consisting of only a few megapixels. Pixels are pulled together into groups of seven and those seven pixels are then condensed into one, so that even though the resulting photograph is only a few megapixel images it is of a better quality than those captured with more traditional five megapixel cameras. For example, Nokia Lumia 1020 uses a 41-megapixel camera to take the original image, however, reduces this to only an output of 5 megapixels. This thus produces a

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