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PRNewswire: OmniVision has combined its OX03A1Y sensor with FPGA-based Arm Mali-C71 ISP for a dual-mode automotive camera module.

"OmniVision's dual-mode image sensor showcases the Mali-C71's ability to process multiple real-time inputs with one pipeline, capturing both human display and computer vision images with a single image sensor, at the highest possible quality," said Tom Conway, director of product management, automotive and IoT Line of Business, Arm.

"Arm's ISP intellectual property is an important part of the automotive ecosystem, and they are a key partner for OmniVision," said Celine Baron, staff automotive product marketing manager at OmniVision. "This collaboration demonstrates the high performance that can be achieved by combining our premium 2.5MP image sensor with Arm's ISP, for automotive applications that need both computer vision and human displays from a single camera module."

OmniVision and Arm used an FPGA emulating the Mali-C71 ISP to simultaneously process images captured by the OX03A1Y sensor for both computer vision and human displays. This sensor uses an RCCB clear color filter pattern to capture high quality images in all lighting conditions. The Mali-C71 then processes the data concurrently, outputting two simultaneous image signals for both human viewing and machine vision.

The OX03A1Y is the industry's first image sensor to feature a 3.2µm pixel with 120dB HDR, dual conversion gain (DCG) and an RCCB color filter. DCG provides motion free HDR to ~85dB, for the best images when vehicles are in motion. The RCCB color filter allows in more light, which, in combination with OmniBSI-2 pixel, produces low-light performance with SNR1 at 0.09 lux, all the while with low power consumption. This is the first sensor to integrate all three capabilities. Additionally, the OX03A1Y is shipping in volume to automotive customers.

The OX03A1Y is available in a small 8.0 x 7.2mm chip-scale package, which is 35% smaller than competing image sensors. Additionally, this image sensor's power consumption is 20% lower than the competition.

The 2.5MP OX03A1Y image sensor integrates advanced ISO 26262 ASIL B functional safety features.

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EurekAlert: NASA is awarding a team of researchers from Rochester Institute of Technology and Dartmouth College a grant to develop a detector capable of sensing and counting single photons for future astrophysics missions. The detector leverages Quanta Image Sensor (QIS) technology and measures every photon that strikes the image sensor. While other sensors have been developed to see single photons, the QIS has several advantages including the ability to operate at room temperature, resistance to radiation and the ability to run on low power.

"This will deliver critical technology to NASA, its partners and future instrument principal investigators," said Don Figer, director of RIT's Center for Detectors, the Future Photon Initiative and principal investigator for the grant. "The technology will have a significant impact for NASA space missions and ground-based facilities. Our detectors will provide several important benefits, including photon counting capability, large formats, relative immunity to radiation, low power dissipation, low noise radiation and pickup, lower mass and more robust electronics."

The project's co-investigators include RIT Assistant Professor Michael Zemcov and Dartmouth Professor Eric R. Fossum. Fossum has focused on inventing the QIS technology while RIT is leading application-specific development that leverages their expertise in astrophysics.

"We're excited for this collaboration with RIT to build upon Dartmouth's proof-of-concept QIS technology to research and develop instrument-grade sensors that can detect single photons in the dimmest possible light," Fossum said. "This has tremendous implications for astrophysics and enables NASA scientists to collect light from extremely distance objects."

The researchers will develop the technology over the next two years. The Center for Detectors will publish results, reports and data processing and analysis software on their website at http://ridl.cfd.rit.edu.

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Radiant Vision, a Konica Minolta company, publishes an interesting comparison of CCD and CMOS cameras in display quality control applications:

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Harvest Imaging Forum to be held in December 2019, in Delft, the Netherlands, is quickly approaching a fully booked status. More than 75 % of the seats have been sold. The Forum topics this year are:

• "On-Chip Feature Extraction for Range-Finding and Recognition Applications" by Makoto IKEDA (Tokyo University, Japan)
• "Direct ToF 3D Imaging : from the Basics to the System" by Matteo PERENZONI (FBK, Trento, Italy)

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ON Semi publishes a webinar "The Current State of Machine Vision Technology: Image Sensor Challenges and Selection."



BusinessWire: ON Semi also announces a 0.3MP machine vision sensor with 2.2um BSI pixels, the 1/10-inch ARX3A0. The new sensor has 1:1 aspect ratio and features ON Semiconductor’s NIR+ technology.

The 560 x 560 pixel sensor can operate at 360fps speed. It consumes less than 19 mW when capturing images at 30 fps, and 2.5 mW when capturing 1 fps.

Gianluca Colli, VP and GM, Consumer Solution Division of Image Sensor Group at ON Semiconductor said: “As we approach an era where Artificial Intelligence (AI) is becoming an integral part of vision-based systems, it becomes clear that we now share this world with a new kind of intelligence. The ARX3A0 has been designed for that new breed of machine, where vision is as integral to their operation as it is ours.”

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China has achieved a lot of advances in cooled MCT and microbolometric imagers, including high resolution up to 2.7K x 2.7K and pixel size down to 10um. These are imagers from Norinco, CETC, iRay, GST, HikVision, and Dali presented at CIOE Show held in Shenzhen, China, last week:

-Norinco picture removed due to the absence of publishing permission-


Thanks to AB for the info!

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Sony unveils 4 new sensors for security and surveillance applications: IMX415-AAMR, IMX455AQK-K, IMX533CQK-D, IMX571BQR-J

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IFNews: According to UBS report, Samsung Galaxy S10 5G cameras, including ToF ones, cost $73. The cameras are the 2nd most expensive component after the display:

Front cameras:

• Selfie Camera
• ToF Depth Camera

Rear cameras:

• Telephoto Camera
• Wide-angle Camera
• Ultra Wide Camera
• ToF Depth Camera

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HuaweiCentral: Huawei presents its new mobile processor Kirin 990 5G at IFA 2019 in Berlin, Germany. One of its most impressive imaging features is the AI-based ability to determine the heart rate and breath rate just from a selfie camera video stream:



Another impressive feature is a real-time video segmentation:



More pictures form the company's IFA presentation:

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DARPA FOcal arrays for Curved Infrared Imagers (FOCII) program is created to expand upon the current commercial trend for visible sensor arrays by extending the capability to both large and medium format midwave (MWIR) and/or longwave (LWIR) infrared detectors. The program seeks to develop and demonstrate technologies for curving existing state-of-the-art large format, high performance IR FPAs to a small radius of curvature (ROC) to maximize performance, as well as curve smaller format FPAs to an extreme ROC to enable the smallest form factors possible while maintaining exquisite performance.

FOCII will address this challenge through two approaches to fabricating a curved FPA. The first involves curving existing state-of-the-art FPAs, while keeping the underlying design intact. The focus of the research will be on achieving significant performance improvements over existing, flat FPAs, with a target radius of curvature of 70mm. The fundamental challenge researchers will work to address within this approach is to mitigate the mechanical strain created by curving the FPGA, particularly in silicon, which is very brittle.

The second approach will focus on achieving an extreme ROC of 12.5 mm to enable a transformative reduction in the size and weight compared to current imagers. Unlike the first approach, researchers will explore possible modifications to the underlying design, including physical modifications to the silicon that could relieve or eliminate stress on the material and allow for creating the desired curvature in a smaller sized FPA. This approach will also require new methods to counter the effects of any modifications during image reconstruction in the underlying ROIC algorithm.


Thanks to TL for the link!

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GlobeNewswire: Lumotive, a Bill Gates-funded LiDAR startup, used Himax’s LCOS display with Lumotive’s patented Liquid Crystal Metasurfaces (LCMs) to improve the performance, reliability and cost of LiDAR systems. Other LiDAR sensors utilize MEMS mirrors or optical phased arrays. However, both of these approaches lack performance due to the small optical aperture of MEMS mirrors and the low efficiency of phased arrays. In a first for LiDAR, Lumotive leverages Himax’s unique, tailor-made LCOS process to convert semiconductor chips into dynamic displays that steer laser pulses based on the light-bending principles of metamaterials.

Lumotive’s LiDAR systems offer performance advantages, including a combination of:

• Large optical aperture (25 x 25 mm) which delivers long range
• 120-degree FoV with high angular resolution
• Fast, random-access beam steering

Leishen Intelligent System presents its broad range of low-cost LiDARs. An automotive grade hybrid LiDAR CH16 3D is priced at $599 in quantities of 10,000:


Update: LeiShen kindly sent me their price list for small quantity purchases:


CoreDAR presents its tiny LiDAR concept:



Hitachi presents its view on LiDAR's role in smart city applications:

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Samsung 5G 8nm Exynos 980 mobile processor supports up to 108MP camera:

"For advanced photography, the Exynos 980 delivers compelling camera performances with resolution support for up to 108-megapixels (Mp). The advanced image signal processor (ISP) supports up to five individual sensors and is able to process three concurrently for richer multi-camera experiences. Along with the NPU, the AI-powered camera is able to detect and understand scenes or objects, according to which the camera will then make optimal adjustments to its settings.

For an immersive multimedia experience, the Exynos 980’s multi-format codec (MFC) supports encoding and decoding of 4K UHD video at 120 frames per second (fps). HDR10+ support with dynamic mapping also offers more detailed and illuminant colors in video content."

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Archiv.org paper "Evaluation of scientific CMOS sensors for sky survey applications" by S.Karpov, A.Bajat, A.Christov, M.Prouza from Czech Academy of Sciences compares Andor cameras based on Fairchild Imaging CIS2051 (Neo camera) and GPixel GSense400BSI (Marana camera) sCMOS sensors:

Scientific CMOS image sensors are a modern alternative for a typical CCD detectors, as they offer both low read-out noise, large sensitive area, and high frame rates. All these makes them promising devices for a modern wide-field sky surveys. However, the peculiarities of CMOS technology have to be properly taken into account when analyzing the data. In order to characterize these, we performed an extensive laboratory testing of Andor Marana sCMOS camera. Here we report its results, especially on the temporal stability and linearity, and compare it to the previous versions of Andor sCMOS cameras. We also present the results of an on-sky testing of this sensor connected to a wide-field lens, and discuss its applications for an astronomical sky surveys.

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GlobeNewswire: Teledyne e2v announces its Flash CMOS sensor family, tailored for 3D laser profiling/displacement applications and high speed, high resolution inspection.

The new Flash sensors feature a 6μm CMOS global shutter pixel which effectively combines high resolution and fast frame rate. They are available in a 4k or 2k horizontal resolution, with respective frame rates of 1800fps and 1500fps (8 bits), and respective readout speeds of 61.4Gbps and 25.6Gbps (the best Gbps/price ratio in the market). The sensors come in a µPGA ceramic package fitting in standard optical formats, APS-like optics in the 4k and C-Mount in the 2k.

Yoann Lochardet, Marketing Manager for 3D at Teledyne e2v said, “We are very pleased to announce the release of the new Flash family of CMOS sensors which were developed after listening closely to the requirements of leading companies in the market. These new sensors feature a unique set of characteristics targeted at 3D laser triangulation applications including; high resolution, very high frame rate, very high readout speed, HDR capability and a large set of additional features. All these capabilities allow our customers to solve the most challenging application demands in 3D laser profiling/displacement such as quality control and 3D measurement.”

Evaluation Kits and samples of Flash 2K and Flash 4K are now available.

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PRNewswire: OmniVision announces the smallest-ever pixel size of 2.2um for a BSI, GS image sensor. The new OG01A sensor combines PureCel Plus-S pixel and Nyxel NIR technology to achieve QE of 40% at 940nm and 60% at 850nm.

The OG01A is well-suited to multiple machine-vision applications, including AR/VR headsets, drones, robots, and SLAM, as well as facial authentication in smartphones and other consumer electronics. This technology is also ideal for automotive in-cabin driver state monitoring and eye tracking.

"The OG01A has the industry's smallest global shutter pixel and provides the best NIR performance in a GS sensor," said Devang Patel, senior staff marketing manager for the security and emerging segments at OmniVision. "There is a growing need for global shutter technology to accurately capture images of moving objects, along with excellent NIR performance and small size, in camera applications such as AR/VR headsets, drones, robots and smartphones. The OG01A delivers the industry's best combination of features for these applications."

The 1.3MP OG01A sensor provides 1280x1024 resolution at 120 fps and 640x480 resolution at 240 fps in a compact 1/5 inch optical format. Samples are available now.

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Panasonic will be providing additional automated facial recognition gates for use at a number of airports in Japan. Without the need for prior registration of biometric data, the system compares photographic data of the traveler’s face in the IC chip embedded in the passport with an image taken at the facial recognition gate to verify identity. According to the Japanese Ministry of Justice, approximately 80% of all Japanese travelers use Panasonic’s facial recognition gates.


Forbes: Hong Kong protesters destroying facial recognition towers in protest at a surveillance state. Meanwhile, Chinese facial recognition company Megvii had secured a $750m fundraise ahead of its IPO on Hong Kong stock exchange. Founded by three Tsinghua University graduates, Megvii is one of the major AI surveillance unicorns in China, alongside SenseTime, Yitu and CloudWalk. Reuters reported at the time that the funding raised Megvii's valuation to "slightly over $4 billion," as it prepared for its IPO in Hong Kong.

BusinessInsider, Petapixel: Hong Kong protesters are using laser pointers in an apparent attempt to blind facial-recognition cameras. At least one reporter posted a video with the damage made to his camera while shooting the protests:




My Modern Met: Avoiding facial recognition becomes an art. A piece of jewelry by Polish designer Ewa Nowak is claimed to confuse AI systems and helps a person to avoid the recognition:


South China Morning Post: China Pharmaceutical University in Nanjing is one of the first higher education institutions in the country to use facial recognition system to monitor the attendance and behavior of students.

“Besides attendance, the system installed in the classroom can provide surveillance of the students’ learning, such as whether they are listening to the lectures, how many times they raise their heads, and whether they are playing on their phones or falling asleep.

The school is taking action to cut down on students skipping class, leaving classes early, paying for a substitute to attend classes for them and not listening in class.”

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ON Semi publishes Arxiv.org paper "Deep Camera: A Fully Convolutional Neural Network for Image Signal Processing" by Sivalogeswaran Ratnasingam.

"A conventional camera performs various signal processing steps sequentially to reconstruct an image from a raw Bayer image. When performing these processing in multiple stages the residual error from each stage accumulates in the image and degrades the quality of the final reconstructed image. In this paper, we present a fully convolutional neural network (CNN) to perform defect pixel correction, denoising, white balancing, exposure correction, demosaicing, color transform, and gamma encoding. To our knowledge, this is the first CNN trained end-to-end to perform the entire image signal processing pipeline in a camera. The neural network was trained using a large image database of raw Bayer images. Through extensive experiments, we show that the proposed CNN based image signal processing system performs better than the conventional signal processing pipelines that perform the processing sequentially."

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2019 International Image Sensor Workshop (IISW) papers are available on-line at the International Image Sensor Society site. The workshop has been held on June 23-27, 2019
in Snowbird, Utah.

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Fraunhofer IOSB publishes MDPI paper "Laser Safety Calculations for Imaging Sensors" by Gunnar Ritt.

"This publication presents an approach to adapt the well-known classical eye-related concept of laser safety calculations on camera sensors as general as possible. The difficulty in this approach is that sensors, in contrast to the human eye, consist of a variety of combinations of optics and detectors. Laser safety calculations related to the human eye target terms like Maximum Permissible Exposure (MPE) and Nominal Ocular Hazard Distance (NOHD). The MPE describes the maximum allowed level of irradiation at the cornea of the eye to keep the eye safe from damage. The hazard distance corresponding to the MPE is called NOHD. Recently, a laser safety framework regarding the case of human eye dazzling was suggested. For laser eye dazzle, the quantities Maximum Dazzle Exposure (MDE) and the corresponding hazard distance Nominal Ocular Dazzle Distance (NODD) were introduced. Here, an approach is presented to extend laser safety calculations to camera sensors in an analogous way. The main objective thereby was to establish closed-form equations that are as simple as possible to allow also non-expert users to perform such calculations. This is the first time that such investigations have been carried out for this purpose."

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Arizona State University team led by Robert LiKamWa explains why image sensor resolution change takes so long on Android and iOS systems:

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Axiv.org paper "Compressive Sampling for Array Cameras" by Xuefei Yan, David J. Brady, Jianqiang Wang, Chao Huang, Zian Li, Songsong Yan, Di Liu, and Zhan Ma from Duke University, Nanjing University, and Kunshan Camputer (?) Laboratory says:

"In the 75 year transition from standard definition to 8K, the pixel capacity of video has increased by a factor of 100. Over the same time period, the computer was invented and the processing, communications and storage capacities of digital systems improved by 6-8 orders of magnitude. The failure of video resolution to develop a rate comparable to other information technologies may be attributed to the physical challenge of creating lenses and sensors capable of capturing more than 10 megapixels. Recently, however, parallel and multiscale optical and electronic designs have enabled video capture with resolution in the range of 0.1-10 gigapixels per frame. At 10 to 100 gigapixels, video capacity will have increased by a factor comparable to improvements in other information technologies."

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Security and Defense Business Review publishes an interview with Jean-François Delepau, CEO of Lynred company formed by merger of Sofradir and ULIS IR businesses. Few quotes:

"Lynred is now the world’s number-two developer of infrared technology in the two fields we serve, and we have an 18% share of the global market. The company boasts 1,000 employees, mostly based in Grenoble, and generates annual revenue of €225 million (43% on the defense market, 34% on the industrial market, 12% on the civil aeronautics and space markets, and 11% on the consumer goods market).

Lynred will pursue a pro-active growth strategy. The military infrared imaging systems market, estimated at $8.5 billion (around €7.6 billion) in 2018, is expected to grow to $14 billion (around €12.5 billion) by 2023. If you extrapolate the data from the industrial and consumer camera market, this market could grow from $2.9 billion (around €2.6 billion) to $4.1 billion (around €3.7 billion) over the same period. This represents potential growth of up to 10% for cameras and systems.

With the government’s support, Lynred is investing €150 million over five years to develop its future generations of infrared detectors. These new IR systems will be designed to meet the needs of autonomous systems for smart buildings (workspace management, energy efficiency), traffic safety, and vehicle cabin comfort. The development work will also encompass very-large-format infrared detectors used in astronomy and space observation and lightweight, compact detectors that can be integrated into portable systems and drones."

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NYTimes, EETimes, Reuters: While Waymo has settled the lawsuit against Uber over stealing its LiDAR secrets, the U.S. Department of Justice filed the personal criminal charges against Anthony Levandowski, accusing the former high-ranking Alphabet Inc. engineer of stealing the company’s LiDAR technology before joining rival Uber Technologies Inc. Levandowski has started another self-driving car technology company since leaving Uber in 2017.

In February 2018, Uber announced to pay $245M worth of its own shares to Waymo to settle the legal dispute.

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IC Insights: Despite an expected slowdown in growth this year and in 2020, the CMOS sensor market is forecast to continue reaching record-high sales and unit volumes through 2023 with the spread of digital imaging applications offsetting weakness in the global economy and the fallout from the U.S.-China trade war.

IC Insights is forecasting an 11% rise in CMOS sensor shipments in 2019 to a record-high 6.1b units worldwide, followed by a 9% increase in 2020 to 6.6b when the global economy is expected to teeter into recessionary territory, partly because of the tariff-driven trade war between the U.S. and China. In 2018, CMOS image sensor revenue grew 14% to $14.2b after climbing 19% in 2017. CMOS sensor sales have hit new-high levels each year since 2011 and the string of consecutive records is expected to continue through 2023, when sales reach $21.5 billion.

Worldwide shipments of CMOS image sensors also have reached eight consecutive years of all-time high levels since 2011 and those annual records are expected to continue to 2023, when the unit volume hits 9.5b. China accounted for about 39% of all image sensors purchased in 2018 (not counting units bought by companies in other countries for system production in Chinese assembly plants). About 19% of image sensors in 2018 were purchased by companies in the Americas (90% of them in the US.)

Camera cellphones continue to be the largest end-use market for CMOS image sensors, generating 61% of sales and representing 64% of unit shipments in 2018, but other applications will provide greater lift in setting annual market records in the next five years. The automotive systems being the fastest growing CMOS sensor application, with dollar sales volume rising by a CAGR of 29.7% to $3.2b in 2023, or 15% of the market’s total sales that year (versus 6% in 2018). After that, the highest sales growth rates in the next five years are expected to be: medical/scientific systems (a CAGR of 22.7% to $1.2b); security cameras (a CAGR of 19.5% to $2.0b); industrial, including robots and the Internet of Things (a CAGR of 16.1% to $1.8b); and toys and games, including consumer-class virtual/augmented reality (a CAGR of 15.1% to $172M).

CMOS sensor sales for cellphones are forecast to grow by a CAGR of just 2.6% to $9.8b in 2023, or about 45% of the market total versus 61% in 2018 ($8.6b). Revenues for CMOS sensors in PCs and tablets are expected to rise by a CAGR of 5.6% to $990M in 2023, while sensor sales for stand-alone digital cameras (still-picture photography and video) are projected to grow by a CAGR of only 1.0% to $1.1b in the next five years.

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TechXplore: Sony and Yamaha Motor unveil SC-1 Sociable Cart, promoted as "a new mobility experience" and based on Sony sensors. There are five 35 mm full-frame CMOS sensors (four directions around the vehicle and one in the vehicle) and two ISX019 1/3.8-inch CMOS sensor embedded cameras.

The image sensors are used to capture surroundings on HD displays in the area where windows would otherwise be. A ToF-based mixed reality technology developed by Sony superimposes computer graphics onto the surroundings on the monitor. "This turns the area that used to be taken up by windows, where passengers could only see the scenery, into an entertainment area."

According to Sony, "analyzing the images obtained via the image sensor with artificial intelligence (AI) enables the information being streamed to be interactive. The AI can determine the attributes (age, gender, etc.) of people outside the vehicle and optimize ads and other streaming info accordingly."

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