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NHK publishes a flyer toward its Open House event traditionally held at the end of May:


The research on back-illuminated small-size image sensors is jointly being conducted with Shizuoka University. The pixel-parallel processing three-dimensional integrated imaging devices research is jointly being conducted with the University of Tokyo. The organic image sensors research is jointly being conducted with Kochi University of Technology.

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Sharp reports the results of its fiscal 2015 year, ended on March 31, 2016. One of the largest product categories "CCD/CMOS Imagers" in the previous reports, now disappears. The camera modules group is reported instead:

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Nuit Blanche: Rice and Cornell Universities publish a paper on CNN integration onto the image sensor:

"ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels" by Huaijin Chen, Suren Jayasuriya, Jiyue Yang, Judy Stephen, Sriram Sivaramakrishnan, Ashok Veeraraghavan, Alyosha Molnar.

Abstract: Deep learning using convolutional neural networks (CNNs) is quickly becoming the state-of-the-art for challenging computer vision applications. However, deep learning's power consumption and bandwidth requirements currently limit its application in embedded and mobile systems with tight energy budgets. In this paper, we explore the energy savings of optically computing the first layer of CNNs. To do so, we utilize bio-inspired Angle Sensitive Pixels (ASPs), custom CMOS diffractive image sensors which act similar to Gabor filter banks in the V1 layer of the human visual cortex. ASPs replace both image sensing and the first layer of a conventional CNN by directly performing optical edge filtering, saving sensing energy, data bandwidth, and CNN FLOPS to compute. Our experimental results (both on synthetic data and a hardware prototype) for a variety of vision tasks such as digit recognition, object recognition, and face identification demonstrate 97% reduction in image sensor power consumption and 90% reduction in data bandwidth from sensor to CPU, while achieving similar performance compared to traditional deep learning pipelines.

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Optics.org: e2v reportes 17% sales growth for its imaging division in its annual report for the year ending March 31, 2016. The company CEO Steve Blair declared himself “delighted” with overall results. At £103.5M, the imaging division’s sales were up from £88.7M in the prior year, growing at a much faster rate than e2v’s other divisions.

CEO Steve Blair and chairman Neil Johnson noted a sharp improvement in profit margins for the imaging division. Recent changes have included the summer 2014 acquisition of Anafocus, and the sale of e2v’s thermal imaging unit.

A year ago e2v said that it had ten “problem contracts” in space imaging, of which four have now been completed and five are due for delivery within 12 months. “We have a strong position in Europe, particularly in CCD sensors, and our offering remains attractive to customers due to its long proven performance in flight,” said the e2v executives.

The increased use of sensors for industrial automation has brought on board some new customers. “We are well positioned to take advantage of the five year plan in China for automation to support the quality drive to 'made in China',” added Blair and Johnson.

Looking to the future, CEO Blair sounded a note of caution regarding the broader macroeconomic environment, but told investors that he still expected solid growth from the imaging division.

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As mentioned in comments, there is a nice video lecture by Mobileye algorithm group leader Uri Rokni on challenges in vision algorithms for autonomous driving:

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BusinessWire: FotoNation, a wholly owned subsidiary of Tessera, partners with Kyocera to develop intelligent vision solutions for automotive applications. As part of the partnership and using FotoNation technology as a foundation, the two companies will jointly develop advanced computer vision solutions for the automotive market.

“FotoNation is focused on delivering complex computational imaging solutions for automotive applications, and together we will develop technologies that will transform the future of driving,” said Norio Okuda, Manager, Kyocera.

“Increasing interest from the automotive industry for vision systems to enhance vehicle safety represents an opportunity for significant growth for FotoNation, driven mainly by adoption of our advanced imaging systems by tier-one automotive suppliers and OEMs,” stated Sumat Mehra, SVP of marketing and business development at FotoNation. “Kyocera has a strong reputation as a leading technology innovator, and we are pleased to be working with them as a valued technology partner to bring these cutting-edge vision solutions to market.”

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MINATEC publishes a promotional Youtube video on its lensless imaging:

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Yahoo: Anitoa, a Menlo Park, CA startup, demonstrates its low cost and portable chemiluminescence reader and applied it successfully with chemiluminescence immunoassay (CLIA). This CMOS-based solution is capable of detecting as low as a few ng/ML of analyte, such as protein macromolecules, in a sample. Applications of this technology ranges from clinical diagnostics to food safety and environmental monitoring.

A key component of Anitoa's portable chemiluminescence reader is its proprietary ULS24 CMOS bio-optical sensor chip with extreme low-light sensitivity. The ULS24 CMOS sensor also eliminates the need for a multi-sites scanning mechanism commonly used by most chemiluminescence readers. At a 5mmX5mm footprint and consumes only 30mW of power, Anitoa's ULS24 is especially well suited for point-of-care diagnostics applications.

Released in September 2014, Anitoa's ULS24 ultra-low light CMOS bio-optical sensor is said to be the first and only commercially available CMOS sensor that has the needed sensitivity to substitute the bulky and expensive photon multiplier tubes (PMT) and cooled-CCDs in a wide range of medical and scientific instruments. The ultra-low light sensitivity (3e-6 lux) of Anitoa's CMOS sensor is crucial for achieving good SNR in imaging molecular interactions based on fluorescent or chemiluminescence signaling principles.

"We are very pleased to see the test results coming back from our lab and our partners' labs showing the effectiveness of CMOS bio-optical sensors in chemiluminescence imaging. This not only validates the CMOS bio-optical sensor's ultra-low-light sensitivity, but also opens up the possibility for a new generation of low cost and portable molecular testing platforms", said Anitoa CEO Zhimin Ding.

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ARM has acquired Apical. Apical is one of the UK’s fastest-growing technology companies and its imaging software are used in more than 1.5 billion smartphones and approximately 300 million other consumer/industrial devices including IP cameras, digital stills cameras and tablets.

The acquisition, closed for a cash consideration of $350 million, supports ARM’s growth strategy by enabling new imaging products for next generation vehicles, security systems, robotics, mobile and any consumer, smart building, industrial or retail application where intelligent image processing is needed. Apical has been founded in 2002 and employs approximately 100 people, mainly at R&D center in Loughborough, UK.

“Computer vision is in the early stages of development and the world of devices powered by this exciting technology can only grow from here,” said Simon Segars, CEO, ARM. “Apical is at the forefront of embedded computer vision technology, building on its leadership in imaging products that already enable intelligent devices to deliver amazing new user experiences. The ARM partnership is solving the technical challenges of next generation products such as driverless cars and sophisticated security systems. These solutions rely on the creation of dedicated image computing solutions and Apical’s technologies will play a crucial role in their delivery.”

“Apical has led the way with new imaging technologies based on extensive research into human vision and visual processing,” said Michael Tusch, CEO and founder, Apical. “The products developed by Apical already enable cameras to understand their environment and to act on the most relevant information by employing intelligent processing. These technologies will advance as part of ARM, driving value for its partners as they push deeper into markets where visual computing will deliver a transformation in device capabilities and the way humans interact with machines.”


Thanks to JC for the link!

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GlobeNewsWire: Mobileye and STMicroelectronics announce that they are co-developing the next (5th) generation of Mobileye's SoC, the EyeQ5, to act as the central computer performing sensor fusion for Fully Autonomous Driving (FAD) vehicles starting in 2020.

To meet power consumption and performance targets, the EyeQ5 will be designed in advanced 10nm or below FinFET technology node and will feature eight multithreaded CPU cores coupled with eighteen cores of Mobileye's next-generation vision processors. These enhancements will increase performance 8x times over the current 4th generation EyeQ4. The EyeQ5 will produce more than 12 Tera operations per second, while keeping power consumption below 5W, to maintain passive cooling at extraordinary performance. Engineering samples of EyeQ5 are expected to be available by first half of 2018.

"EyeQ5 is designed to serve as the central processor for future fully-autonomous driving for both the sheer computing density, which can handle around 20 high-resolution sensors and for increased functional safety," said Prof. Amnon Shashua, cofounder, CTO and Chairman of Mobileye. "The EyeQ5 continues the legacy Mobileye began in 2004 with EyeQ1, in which we leveraged our deep understanding of computer vision processing to develop highly optimized architectures to support extremely intensive computations at power levels below 5W to allow passive cooling in an automotive environment."

"Each generation of the EyeQ technology has proven its value to drivers and ST has proven its value to Mobileye as a manufacturing, design, and R&D partner since beginning our cooperation on the EyeQ1," said Marco Monti, EVP and GM of Automotive and Discrete Group, STM. "With our joint commitment to the 5th-generation of the industry's leading Advanced Driver Assistance System (ADAS) technology, ST will continue to provide a safer, more convenient smart driving experience."

EyeQ5's proprietary accelerator cores are optimized for a wide variety of computer-vision, signal-processing, and machine-learning tasks, including deep neural networks. Autonomous driving requires fusion processing of dozens of sensors, including high-resolution cameras, radars, and LiDARs. The sensor-fusion process has to simultaneously grab and process all the sensors' data. For this purpose, the EyeQ5's dedicated IOs support at least 40Gbps data bandwidth.

Engineering samples of EyeQ5 are expected to be available by first half of 2018. First development hardware with the full suite of applications and SDK are expected by the second half of 2018.

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BusinessWire: Lattice announces the industry’s first CrossLink programmable bridging device that supports leading protocols for mobile image sensors and displays. Systems with embedded cameras and displays often do not have the right type or number of interfaces, which can be resolved using a bridge.

The CrossLink device’s features include:

• World’s fastest MIPI D-PHY bridging device that delivers up to 4K UHD resolution at 12 Gbps bandwidth.
• Supports popular mobile, camera, display and legacy interfaces such as MIPI D-PHY, MIPI CSI-2, MIPI DSI, MIPI DPI, CMOS, and SubLVDS, LVDS and more.
• Industry’s smallest package size with a 6 mm2 option.
• Lowest power programmable bridging solution in active mode.
• Built-in sleep mode.

“The latest wave of image capture and display technology, including drones and VR, is creating real industry excitement. Combining these new technologies with a global base of 3.7 billion smartphones and tablets that’s set to rise more than 30 percent by 2020, all equates to a wide variety of interfaces that must be integrated to ensure compatibility,” said Carl Hibbert, associate director of entertainment content and delivery, Futuresource Consulting. “The ability to manage these interfaces through a low cost, low power and small footprint bridging solution is essential.”

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Himax Q1 2016 earnings report updates on the company's image sensor business:

"It is also worth highlighting that our CMOS image sensor product line bottomed out in the first quarter, rebounding from its trough in 2015.

Looking into the second quarter, there will be mass production of several design wins for notebooks and increased shipments for multimedia applications. In recent press releases and the last earnings call, we briefly introduced our new smart sensor product lines targeting new applications across smartphones, tablets, AR/VR devices, IoT and artificial intelligence. These include the ultra-low-power QVGA CMOS image sensor and the Diffractive Optical Element (“DOE”) integrated WLO laser diode collimator to be paired with a Near Infrared (NIR) sensor.

We believe the former is by far the lowest power CIS in the industry with similar resolution. It can be applied in a constant state of operation, enabling “always on”, contextually aware, computer vision capabilities.

Regarding DOE integrated WLO laser diode collimator with NIR sensor, we believe this is the most effective total solution for 3D sensing and detection in the smallest form factor. This breakthrough allows 3D image sensing feature to be easily integrated into next-generation consumer electronics. Currently, we are making good progress and have seen encouraging and increasing customer responses. We will report the developments in this new territory in due course."

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Nikkei: Nidec Copal claims ti has developed the world's smallest, thinnest and most lightweight 16MP camera module for mobile devices measuring 8.5 x 8.5 x 4.2 mm and weghting about 0.57g. The module is based on a 16MP 1/3.1-inch CMOS sensor with 1.0μm pixels. The module has an AF and F1.9 aperture. Nidec Copal plans to start volume production in the fall of 2016.

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Pixart Q1 2016 report shows that the company's sales are down 5.8% YoY. The net income is down by 69.9% YoY.

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Aphesa publishes its presentation at Caeleste Workshop,a part of SPIE Photonics Europe in Brussels in April 2016. A few slides from the presentation:

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Sony publishes the 4th update on its recovery from Kumamoto fab damage:

• Operations at Sony Kumamoto Technology Center (located in Kikuchi Gun, Kumamoto Prefecture), which is the primary manufacturing site of image sensors for digital cameras and security cameras, had been suspended due to the impact of the earthquakes.
• However, as of May 9, 2016, testing operations, which are one of the back-end processes carried out on the upper layer of the building, have resumed and other back-end processes, such as assembly, are also expected to restart sequentially beginning May 17, 2016.
• Wafer processing operations located on the lower layer of the building are expected to restart sequentially beginning May 21, 2016.
• Although there was a delay in the supply of components to Sony from certain third-party suppliers that also have manufacturing facilities in the Kumamoto region, inventory adjustments have been made and a timeframe for regaining supply levels is now in place, so no material impact is anticipated on Sony's business operations.
• The impact on Sony's consolidated results due to the effect of the earthquakes, including from opportunity losses, as well as expenses for recovery and reinforcement work, continues to be evaluated.

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Imec publishes flyer of Argus, a BSI TDI embedded CCD imager prototype featuring >90% QE and monolithic integration of a CCD module on CMOS for machine vision, remote sensing, life sciences, and scientific applications:

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Cadence publishes a Youtube video presenting its Tensilica P6 Vision DSP:

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Imec publishes a preliminary data for its dual shutter Mantis image sensor utilizing high QE BSI process:

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Open-source Sensors journal publishes paper "Analysis of Subthreshold Current Reset Noise in Image Sensors" by Nobukazu Teranishi. The analysis also includes a tapered reset with a feedback amplifier:

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Nikkei reports that Bosch-baked event-driven sensor developer Chronocam has already been employed by major automakers based in Europe and the US for, as a starter, ADAS and is expected to debut in the market in 2019. The company says that its technology makes it easy to match stereo images taken by the two cameras to obtain range information at a high speed and with a low power consumption:

Chronocam stereo camera prototype for automotive applications

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DJI publishes a Youtube video showing the Phantom 4 capabilities provided by its cameras and vision processing system:

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PRNewswire: Continental unveils a project that adds the detection zone of gestures on the steering wheel. This is possible due to a TOF sensor, which is integrated into the instrument cluster. Using this approach, the solution minimizes driver distraction and further enhances the development of the holistic human-machine interface.

By swiping up and down, the driver scrolls through the board computer menu

To select submenus of an app or to find the favorite song, the driver swipes horizontally on the gesture panel.

By thumb double typing on the gesture panel, the music starts playing.

With a little wave of the hand the driver can accept an incoming call. A wave with the other hand rejects it.

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CRC Press publishes "Analog Electronics for Radiation Detection" book edited by Renato Turchetta.

Some of the interesting chapters on image sensing:

• Analog Electronics for HVCMOS Sensors
  Ivan Peric
• Analog Electronics for Radiation Detection
  Juan A. Leñero-Bardallo and Ángel Rodríguez-Vázquez
• Low-Noise Detectors through Incremental Sigma-Delta ADCs
  Adi Xhakoni and Georges Gielen
• Time-to-Digital Conversion
  Yasuo Arai
• Designing Photon-Counting, Wide-Spectrum Optical Radiation Detectors in CMOS-Compatible Technologies
  Edoardo Charbon and Chockalingam Veerappan
• CMOS Image Sensors for Radiation Detection
  Nicola Guerrini

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Rambus publishes a couple of Youtube videos on its Lensless image sensors (LSS). The first one is about applications while the second one demos a thermal LSS operation:

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CEI-Europe posts a nice iconographic comparing CCD with CMOS sensor. As it's too large to post it here, there are just few cuts:


Thanks to AL for the link!

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According to Statista, CMOS sensors is the main sensing device in IoT:

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Mobileye quarterly earnings transcript reveals the company's plans on the new generation camera:

Amnon Shashua, Mobileye NV - Co-Founder, CTO & Chairman:

"So we have talked three sensor modalities, they are cameras, radars, and LADARS. Cameras are the only sensor that can also sense appearance, texture in addition to sensing shape. The other two sensors are primarily focused on sensing shape. Each sensor modality is anticipated to grow, cameras would be growing towards added resolution. We are working with a camera with imagery suppliers on a new design by 2019, we'll have 7.4 megapixel imagers for supporting autonomous driving."

Thanks to DS for the link!

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ON Semi's KAE-02150 EMCCD sensor was named a Gold-level winner of the Vision Systems Design 2016 Innovators Award, which recognizes the most innovative products and services in the Vision and Image Processing industry.

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IC Insights: CMOS sensors are in the middle of an unprecedented string of record-high annual sales thanks to the rapid spread of embedded digital imaging technology into a wide range of end-use applications that go far beyond smartphones and stand-alone cameras. According to IC Insights’ 2016 O-S-D Report—A Market Analysis and Forecast for Optoelectronics, Sensors/Actuators, and Discretes, automotive systems are forecast to be the fastest growing application for CMOS image sensors with worldwide sales rising by a compound annual growth rate (CAGR) of 55% in the next five years to $2.2 billion in 2020, or about 14% of the market’s projected $15.2 billion total.

After the automotive segment, the highest growth rates for CMOS image sensor sales in the next five years are expected to be in security and surveillance (a CAGR of 36% to $912 million), medical/scientific applications (a CAGR of 34% to $867 million), toys/video games (a CAGR of 32% to $274 million), and industrial systems (a CAGR of 18% to $897 million). Automotive electronics is the next major market opportunity for CMOS sensors.

Camera phones image sensor segment is expected to grow by a CAGR of just 1% to $7.3 billion in 2020, or 48% of the market total versus 70% in 2015. Revenues for CMOS sensors in camera modules used in PCs and tablet computers are projected to rise by a CAGR of about 6% to $973 million in 2020, while sensor sales for stand-alone digital cameras are expected to shrink by a CAGR of -2% to 623 million in five years, according to IC Insights’ report.

Worldwide CMOS image sensor revenue grew 12% in 2015 to $9.9 billion, which was the fifth consecutive record-high annual sales volume achieved by this product category since 2011. CMOS image sensors continue to set record-high sales levels for at least another five years in a row, growing by a CAGR of 9.0% from 2015 to 2020. In the previous five-year period (2010-2015), CMOS sensor sales increased by a CAGR of 17.0% with much of that strong annual growth rate being driven by the market’s recovery from the severe economic recession in 2008-2009 and the emergence of new embedded camera applications and image-recognition system interfaces, which are now fueling the next wave of growth in imaging devices.

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