Monday, October 14, 2019

IHS Markit Market Data

Korea Joongang Daily quotes IHS Markit data on CIS market shares:

IFNews quotes IHS Markit report on smartphone camera market: "IHS Market states that though global smartphone market declines, yet the camera market is growing in 2019. Considering the image sensor size is increasing 40%~50% while upgrade from 16MP to 48MP or even 64MP, and total wafer demand will increase about 50% in 2019."

Sunday, October 13, 2019

Caeleste HDR, GS, BSI, Radhard Imager

Caeleste announces its presentations at Toulouse CMOS Image Sensors Workshop to be held on November 26-27, 2019. One of them is about ELFIS project - a rad-hard, GS, true HDR, BSI image sensor, already reported earlier:

Saturday, October 12, 2019

Two World's Largest Security Camera Companies Added to the US Sanctions List

Nikkei, Bloomberg, IPVM: China's largest security camera makers and face recognition AI companies have been added to the US trade sanctions list.

Hikvision is the world's largest security camera company. Hikvision has a close cooperation with Sony. The rumor is that Sony makes special image sensor versions optimized to Hikvision requirements that are exclusive to the company. From the company's web site:

"According to yearly independent research data from IHS Markit, Hikvision accounted for 19.5% of market share in global video surveillance industry in 2015, up from 4.6% in 2010, and has been ranked the No.1 market share leader globally for video surveillance equipment for five consecutive years. In 2015, Hikvision was ranked first in EMEA market with 12.2% market share, and was ranked second in Americas market with 7.3% market share.

Hikvision has established partnerships with world technology leaders including Intel, Texas Instruments, Ambarella, Sony, Hisilicon, Western Digital and Seagate.

From Dahua web site: "Dahua Technology has been ranked 2nd in the global CCTV & video surveillance equipment market according to an IHS report since 2014, and was ranked 2nd in “2018 a&s Security 50”."

According to the recent IDC report, "China's video surveillance market is relatively concentrated, with the top three vendors (Hikvision, Dahua and Uniview) having a combined market share of 56.4%. The concentrated market enhances top vendors' economies of scale effects."

Alibaba-backed Megvii filed for an IPO this summer of at least $500m in Hong Kong, while SenseTime raised $620m in a second round of funding in just two months last year and is one of the world's most valuable unicorns in artificial intelligence.

Friday, October 11, 2019

Veoneer on Automotive Thermal Camera Challenges

Veoneer presents some of the challenges in design and use of thermal camera in automotive applications:

NIT Presentation on InGaAs Imaging in Space Applications

New Imaging Technologies presentation "SWIR imaging and space applications" by Simon Ferré shows the company's solutions for space:

Counterpoint Research: Sony and Samsung Captured 85% of Smartphone CIS Market

Counterpoint Research publishes its analysis of smartphone image sensor market. Its key points are:
  • An annual revenue growth rate of up to 10%
  • The total revenue from smartphones is likely to grow above $12b
  • Smartphones is the single largest end-market accounted for nearly 70% of the overall CIS revenue in 2018
  • In 2018, each smartphone featured 2.4 image sensors on average
  • By 2020, this number is expected to be over three
  • In 1H 2019, over US$5b worth of CIS were sold in smartphones.
  • Sony Image Sensor Solutions accounted for over 20% of Sony’s total operating income during the quarter ending June 2019
  • In Q2 2019, Sony earned 195 billion yen or over US$1.8b from image sensor sales
  • Sony is planning to invest in CIS ~700 billion yen (~$6.5b) during the period of 2018~2020
  • Samsung LSI is to invest KRW 133 trillion (roughly $10.8b) for non-memory semiconductors
  • Samsung CIS business stands at ~$2.46b in terms of revenue
  • Samsung’s image sensors are used in its own phones as well as in Chinese brands like Xiaomi, Vivo, and OPPO
  • During H1 2019, Sony and Samsung together occupied approximately 85% of sales revenue
  • Smaller players like OmniVision and SK Hynix are primarily used in front cameras or multi-camera setups as supplementary sensors
  • SK Hynix plans to transform part of its DRAM fabs to production of CIS

Thursday, October 10, 2019

Fujitsu 3D Camera-powered AI Gives Scores to Gymnasts

Fujitsu publishes a video on how its 3D camera and AI help with scores in gymnastics and more:

LiDAR Interviews at AutosensTV

Autosens Brussels publishes interviews with Aeye, Fraunhofer, Xenomatix, and Hamamatsu.

IEDM 2019: Sony Presents 48MP All-pixel PDAF, 3-layer Organic, and InGaAs SWIR Sensors, Samsung finFETs for >100MP CIS, Omnivision Voltage Domain GS

IEDM 2019 program has briefly come up online and put down shortly after that yesterday with a promise to be published again in mid-October. Many interesting image sensor papers have been exposed for this short time:

  • A 1/2inch 48M All PDAF CMOS Image Sensor Using 0.8µm Quad Bayer Coding 2×2OCL with 1.0lux Minimum AF Illuminance Level
    Tatsuya Okawa, Susumu Ooki, Hiroaki Yamajo, Masakazu Kawada, Masayuki Tachi, Kazuhiro Goi, Takatsugu Yamasaki, Hiroki Iwashita, Sony Semiconductor manufacturing Corporation, Masahiko Nakamizo, Takayuki Ogasahara, Yoshiaki Kitano, Keiji Tatani, Sony Semiconductor Solutions Corporation, Sony Semiconductor Manufacturing Corporation
    We created the world's first all PDAF CMOS image sensor using 2x2 on-chip lens architecture. That had 1/2 inch 48M pixels with 0.8µm Quad Bayer coding for high resolution and HDR function, and all PDAF pixels achieved a minimum AF illuminance level of 1 lux.
  • Three-layer Stacked Color Image Sensor With 2.0-μm Pixel Size Using Organic Photoconductive Film
    Togashi Hideaki, Sony Semiconductor Solutions Corporation
    A three-layer stacked color image sensor was formed using an organic film. The sensor decreases the false color problem as it dose not require demosaicing. Furthermore, with the 2.0-μm pixel image sensor, improved spectral characteristics owing to green adsorption by the organic film above the red/blue photodiode, were successfully demonstrated.
  • High-definition Visible-SWIR InGaAs Image Sensor using Cu-Cu Bonding of IIIV to Silicon Wafer
    Shuji Manda, Sony Semiconductor Solutions Corporation
    We developed a back-illuminated InGaAs image sensor with 1280 x 1040 pixels at 5-um pitch by using Cu-Cu hybridization connecting different materials, a III-V InGaAs/InP of photodiode array, and a silicon readout integrated circuit (ROIC). A prototype device showed high sensitivity at visible to SWIR wavelengths and low dark current.
  • Nanophotonics contributions to state-of-the-art CMOS Image Sensors (Invited)
    Sozo Yokogawa, Sony Semiconductor Solutions Corporation
    Recent progress of Back-illuminated CMOS image sensors (BI-CISs), focusing on their pixel improvements with the design of optical properties using subwavelength sizescale strcutures and photonics technologies, are reviewed. These technologies contribute not only improving BI-CIS basic performance but also adding new functions for versatile sensing applications.
  • 14nm FinFET Process Technology Platform for Over 100M Pixel Density and Ultra Low Power 3D Stack CMOS Image Sensor
    Donghee Yu, Choongjae Lee, Myoungkyu Park, Samsung, Samsung Electronics
    CMOS Image Sensor(CIS) products need higher voltage device and better analog characteristics than conventional SOC & Logic products. This work presents newly developed 14nm FinFET process with 2.xV high voltage FinFET device characteristics showing excellent analog and low power digital characteristics comparing to 28nm planar process.
  • A 0.8 µm Smart Dual Conversion Gain Pixel for 64 Megapixels CMOS Image Sensor with 12k e- Full-Well Capacitance and Low Dark Noise
    Donghyuk Park, Seung-Wook Lee, Jinhwa Han, Dongyoung Jang, Heesang Kwon, Seungwon Cha, Mihye Kim, Haewon Lee, Sungho Suh, Woong Joo, Yunki Lee, Seungjoo Nah, Heegeun Jeong, Bumsuk Kim, Sangil Jung, Jesuk Lee, Yitae Kim, Chang-Rok Moon, Yongin Park, Samsung Electronics
    A 0.8 μm-pitch 64 megapixels CIS has been demonstrated for the first time. 6k e- full-well capacity (FWC) was achieved, and the advanced color filter isolation was introduced. Dual conversion gain enhanced the Tetracell FWC to 12k e-. Highly refined deep trench isolation and photodiode also improved dark noise characteristics.
  • Low-Latency Interactive Sensing for Machine Vision (Invited)
    Paul K. J. Park, Jun-Seok Kim, Chang-Woo Shin, Hyunku Lee, Weiheng Liu, Qiang Wang, Yohan J. Roh, Jeonghan Kim, Yotam Ater, Hyunsurk Ryu, Samsung Electronics
    We introduce the low-latency interactive sensing and processing solution for machine vision applications. The event-based vision sensor can compress the information of moving objects in cost-effective way, which in turn, enables the energy-efficient and real-time processing in various applications such as person detection, motion recognition, and Simultaneous Localization and Mapping.
  • A 2.2µm Stacked Back Side Illuminated Voltage Domain Global Shutter CMOS Image Sensor
    Geunsook Park, Alan Hsiung, Keiji Mabuchi, Jingming Yao, Zhiqiang Lin, Vincent Venezia, Tongtong Yu, Yu-Shen Yang, Tiejun Dai, Lindsay Grant, OmniVision
    This paper introduces a 2.2µm stacked BSI voltage domain global shutter CMOS image sensor displaying over 100dB shutter efficiency, as well as high NIR-QE of 38% at 940nm, 60% MTF Ny/2 at 940nm with stacked pixel level connections, high density MIM capacitors, and Full back-side Deep Trench Isolations.
  • A Highly Reliable Back Side Illuminated Pixel against Plasma Induced Damage
    Yolene Sacchettini, Jean-Pierre Carrère, Célestin Doyen, Stéphane Ricq, Romain Duru, Vincent Goiffon, Pierre Magnan, Kristell Courouble, STMicroelectronics / ISAE-Supaero, STMicroelectronics, Univ. of Toulouse
    Plasma process interaction with BSI image sensor is for the first time presented. The backside dielectrics properties modulate the damage, this was characterized by measuring the dielectrics charge and the interface state density. Metal oxides present a better hardiness to plasma damage due to their negative charge even after plasma.
  • Flexible, Active-Matrix Flat-Panel Image Sensor for Low Dose X-ray Detection Enabled by Integration of Perovskite Photodiode and Oxide Thin Film Transistor
    Taoyu Zou, Changdong Chen, Ben Xiang, Ya Wang, Chuan Liu, Shengdong Zhang, Hang Zhou, Peking University Shenzhen Graduate School, Sun Yat-sen University
    An image sensor based on low-cost two-step deposited perovskite photodiode arrays and oxide (IGZO) TFTs is demonstrated for direct and indirect X-ray imaging applications. The system can be fabricated on flexible substrates, and the perovskite photodiode exhibits a significant direct X-ray response, reaching a sensitivity of ~887 μCGy-cm^–2
  • Intelligent Vision Systems – Bringing Human-Machine Interface to AR/VR (Invited)
    Chiao Liu, Andrew Berkovich, Song Chen, Hans Reyserhove, Syed Shakib Sarwar, Tsung-Hsun Tsai, Facebook Reality Labs
    An all-day wearable AR/VR device in a glasses form factor needs new input modalities. The candidates include voice, eye gazing, hand/body/head gestures, and BCI. This paper describes computer vision based modalities and the sensor and system specifications, and propose solutions to the extremely stringent power, form factor and performance challenges.
  • High-speed Image Processing Devices and Its Applications (Invited)
    Masatoshi Ishikawa, The University of Tokyo
    We have developed a high-speed and low-latency image processing devices and systems. In this talk, their architectures and applications such as robotics, factory automation, fuman interface, bio/medical applications, 3D achieving, and vehicles will be explained by using videos.

IEDM tipsheet explains the impact of Sony InGaAs integration paper:

"Demand for imaging in the short-wavelength infrared range (SWIR, or 1,000-2,000nm wavelengths) has been increasing for industrial, science, medical, agricultural and security purposes. InGaAs has been used to build SWIR sensors because it can absorb light in this range that silicon cannot. With conventional back-illuminated InGaAs sensors, each pixel of a photodiode array is connected to a readout circuit on a silicon wafer by means of a microbump. But it’s difficult to scale these bumps, and so creating finepitch pixel arrays for greater image definition is difficult. A Sony team will describe an architecture in which each pixel in an InGaAs/InP photodiode array is connected to the readout circuit not with microbumps, but by means of copper-to-copper bonding, resulting in a much tighter pitch. They used the technique to build a prototype 1280 x 1024-pixel array with a 5µm pitch. Also, thinning of the InP layer and process optimization yielded a sensor that demonstrated high sensitivity and low dark current, respectively. The researchers say this work paves the way for high-definition SWIR imaging."

Wednesday, October 09, 2019

Nature Journal on Fooling Deep-Learning AI

Nature article "Why deep-learning AIs are so easy to fool" by Douglas Heaven says:

"A self-driving car approaches a stop sign, but instead of slowing down, it accelerates into the busy intersection. An accident report later reveals that four small rectangles had been stuck to the face of the sign. These fooled the car’s onboard artificial intelligence (AI) into misreading the word ‘stop’ as ‘speed limit 45’.

Such an event hasn’t actually happened, but the potential for sabotaging AI is very real. Researchers have already demonstrated how to fool an AI system into misreading a stop sign, by carefully positioning stickers on it. They have deceived facial-recognition systems by sticking a printed pattern on glasses or hats.

These are just some examples of how easy it is to break the leading pattern-recognition technology in AI, known as deep neural networks (DNNs).

“There are no fixes for the fundamental brittleness of deep neural networks,” argues François Chollet, an AI engineer at Google in Mountain View, California. To move beyond the flaws, he and others say, researchers need to augment pattern-matching DNNs with extra abilities: for instance, making AIs that can explore the world for themselves, write their own code and retain memories. These kinds of system will, some experts think, form the story of the coming decade in AI research.

SPAD Progress Review in Nature Journal

Nature Light: Science and Applications publishes a paper "Single-photon avalanche diode imagers in biophotonics: review and outlook" by Claudio Bruschini, Harald Homulle, Ivan Michel Antolovic, Samuel Burri, and Edoardo Charbon from EPFL and TU Delft. A draft version of the paper has been published earlier in

"A host of architectures have been investigated, ranging from simpler implementations, based solely on off-chip data processing, to progressively “smarter” sensors including on-chip, or even pixel level, time-stamping and processing capabilities. As the technology has matured, a range of biophotonics applications have been explored, including (endoscopic) FLIM, (multibeam multiphoton) FLIM-FRET, SPIM-FCS, super-resolution microscopy, time-resolved Raman spectroscopy, NIROT and PET. We will review some representative sensors and their corresponding applications, including the most relevant challenges faced by chip designers and end-users. Finally, we will provide an outlook on the future of this fascinating technology."

Once we talk about SPADs research, EPFL and Weizmann Institute of Science publish paper "Quantum correlation measurement with single photon avalanche diode arrays" by Gur Lubin, Ron Tenne, Ivan Michel Antolovic, Edoardo Charbon, Claudio Bruschini, and Dan Oron.

"Progress in single photon avalanche diode (SPAD) array technology highlights their potential as high performance detector arrays for quantum imaging and photon number resolving (PNR) experiments. Here, we demonstrate this potential by incorporating a novel on-chip SPAD array with 55% peak photon detection probability, low dark count rate and crosstalk probability of 0.14% per detection, in a confocal microscope. This enables reliable measurements of second and third order photon correlations from a single quantum dot emitter. Our analysis overcomes the inter-detector optical crosstalk background even though it is over an order of magnitude larger than our faint signal. To showcase the vast application space of such an approach, we implement a recently introduced super-resolution imaging method, quantum image scanning microscopy (Q-ISM)."

Autosens Brussels Interviews: Sony, Espros, Lumentum, FLIR

Autosens publishes an interview with Bjorn Meyer, Head of Automotive Semi-conductor Sales at Sony Europe:

Interview with Beat de Coi, CEO of ESPROS Photonics:

Angela Suen, Product Line Manager at Lumentum, talks about their FMCW LiDAR:

Mike Walters, VP of Product Management at FLIR, talks about automotive thermal cameras:

TechInsights: iPhone 11 Pro Max Cameras Cost $73.5

TechInsights publishes its estimation of Apple iPhone 11 Pro Max components. The cameras appear to be the post expensive part at $73.50. Incidentally, UBS has the same cost estimation for Samsung Galaxy S10 5G cameras.

EETimes publishes SystemPlus teardown analysis of iPhone if iPhone 11 pointing to the cameras as one of the major differences from the previous generation iPhone XR:

MIPI Publishes Automotive Market White Paper

MIPI Alliance publishes white paper on automotive market:

"A key automotive sensor is the optical camera, which leverages technologies from the billions of cameras developed for the smartphone market. A look at the automotive camera market reveals this explosive growth on the early roads to automation. As shown in Figure 3, studies predict the automotive camera market will grow to $7.5 billion in annual revenue by 2023, with compound annual growth of 24.3% from 2018 to 2023. Taking the view out further, annual revenue for all ADAS technologies is predicted to reach more than $65 billion by 2026.

Estimates of the number of cameras per car vary widely, as shown in Figure 4, but production volume of hundreds of millions of cameras per year is reminiscent of the large volumes seen in smartphones. Current estimates are 8-12 cameras per car in the immediate future.

Tuesday, October 08, 2019

US Authorities Clear Omnivision Acquisition by Will Semiconductor

I missed this news at the time. Global Trade and Sanctions Law site reports:

"The Committee on Foreign Investment in the U.S. (CFIUS) has cleared the acquisition of Beijing OmniVision Technologies Co., Ltd. by Shanghai Will Semiconductor Co., a PRC-listed company, according to an April 16, 2019, filing with the securities regulators in China.

It is possible this transaction was the second step of an original plan to list the assets of OmniVision in China, and CFIUS was told in 2015 about the plan. It is therefore possible there is less here than meets the eye.

As Will Semiconductor's document states, CIFIUS has declined the approval several times since 2015, before finally allowing it this year.

Monday, October 07, 2019

OmniVision 12MP Sensor with HDR Optimized for Ultra Wide Angle Performance

PRNewswire: OmniVision announces the OV12D, a 1.4um 12 MP image sensor with selective conversion gain (SCG) for balance between low-light image quality and HDR. The OV12D features a large 1/2.4" optical format, on-chip 4-cell remosaic color filter, PDAF and extra pixels for 4K2K video EIS.

According to TSR, the number of smartphones with two or three main cameras will grow from just 8% of the market in 2017, to over 20% by 2022, when the estimated total market size will be 5.5 billion phones. Additionally, Yole Développement predicts that, on average, there will be three cameras per smartphone by 2022.

"With multiple world-facing cameras becoming more common in premium smartphones, manufacturers are looking to not only increase the image quality of those cameras, but also to maximize their applications, in order to further differentiate their products," said Arun Jayaseelan, senior marketing manager at OmniVision. "The OV12D sensor leverages OmniVision's advanced pixel technologies and HDR expertise to enable mobile phone makers to use their ultra wide cameras to capture premium quality video with on-chip, 3-exposure HDR, even in low light conditions."

SCG allows the pixel conversion gain to be dynamically switched between low and high, depending on the scene being captured. When capturing images under low light conditions or with dark areas, high conversion gain can help lower noise and improve the signal-to-noise ratio, when compared with a traditional low conversion gain pixel. Likewise, when set to low conversion gain, the sensor has a higher full well capacity, which helps to provide more detail when capturing scenes under bright light. This improves the signal-to-noise ratio under bright light as well as the pixel's overall dynamic range.

The OV12D is a native 16:9 aspect ratio image sensor that uses a 4-cell color filter pattern. It has on chip 4-cell to Bayer remosaic, in order to provide 4K video at 60fps with 20% additional pixels for EIS. In a 4-cell binned mode, it can output a 3MP/1080p resolution with 20% additional pixels for EIS video and images at four times the sensitivity. Additionally, it supports 3-exposure HDR with on-chip combination and tone mapping. This sensor also supports both CPHY and DPHY interfaces, and can output 12MP 16:9 captures at 60fps, 4K video at 60fps and 1080p video at 240fps.

OV12D samples are available now.

Sunday, October 06, 2019

Sony Future of Image Sensing with RISC-V

Sony LSI Design Executive Deputy President Hideki Yoshida's presentation at RISC-V Day Tokyo 2019 on Sept. 30 is titled "Future of Image Sensing with RISC-V." The presentation details on Sony plans of AI integration onto image sensors and also says that Sony is going to pursue "a recurring revenue business model:"

The presentation also shows an updated Sony Semiconductor org chart and the market segmentation and trends:

Saturday, October 05, 2019

Theses from Singapore

Nanyang Technological University, Singapore, publishes a 2015 MSc thesis "Low-power column-parallel ADC for CMOS image sensor by leveraging spatial likelihood in natural scene" by Lifen Liu.

"In this thesis, a new operating method is proposed, which takes into account spatial likelihood in natural scenes. In the proposed method, the MSBs of selected pixel would be predicted before the ADC operation, based on that pixel’s neighbor pixels in the previous row. Because there is strong correlation between consecutive rows in most natural scenes, pre-ADC pixel estimation could save bits in ADC conversion cycles. The total number of ADC conversions would effectively be reduced, resulting in lower power consumption. This method was verified in extensive Matlab simulations, where ADC conversion cycles were reduced by up to 20%-30% for most natural scenes and a saving of up to 29.49% was achieved in switching energy for a 512×512 resolution Lena image."

A 2017 PhD thesis "Low power feature-extraction smart CMOS image sensor design" by Xiangyu Zhang proposes event-based sensor that does not require export of asynchronous pixel addresses to external processor:

"The aim of this work is to design a smart CMOS image sensor that can extract and process motion features on the same chip so as to simplify the entire visual system with minimal computation burden. In order to achieve this ultimate goal, several smart motion-detection image sensors have been developed."

A 2016 PhD thesis "Time-delay-integration CMOS image sensor design for space applications" by Hang Yu proposes:

"(1) A TDI CMOS image sensor was proposed with dynamic pipeline adjacent pixel signal transfer. Following the operation of conventional TDI, the photo signal will be shifted stage by stage and a given photodiode will be reset by the previous-stage photo signal. Meanwhile, this TDI sensor can also configure effective TDI stages for dynamic range and signal-to-noise ratio optimization, as well as the signal transfer direction to compensate for the vibrations. (2) A TDI architecture with single-ended column-parallel signal accumulators was proposed. The TDI operation will be conducted by the off-pixel accumulators, whereby all the photo signals of each TDI stage will be read out after exposure. Accordingly, a 256×8-pixel prototype sensor was designed and fabricated."

Friday, October 04, 2019

Melexis 3rd Gen ToF Sensors

Autosens Brussels publishes an interview with Cliff De Locht, Product Marketing Manager at Melexis, on the company's 3rd generation of automotive ToF sensors:

Yole: Q2 2019 Exceeded Expectations, But Only in Mobile

Yole Developpement, i-Micronews: “Q2 2019 has exceeded our expectations, with +7% but there is little good news beyond mobile,” announces Pierre Cambou, Principal Analyst, Imaging at Yole Développement.

In the immediate future, Yole expects CIS quarterly sales to reach US$4.6 billion in the fourth quarter, mirroring the expected 10% YoY growth rate for 2019. This is an incredible double-digit growth prospect, especially in the context of mobile saturation and overall industry cyclical recession.

Yes, Yole’s analysts can confirm: CIS definitely has its own growth engine – an engine powered by the proliferation of cameras in mobile, which have hit new heights in 2019 since most high-end flagships deliver 5 – 6 cameras per phone. Yole expects this trend to continue over the next 3 – 4 years, before coming to a somewhat abrupt end. Analysts have arbitrarily set their YoY growth expectation at 1% in 2024 to bring this insight to light, and chase away the trolls if for no other reason.

If we peer below the CIS market’s surface, things begin to look way more interesting – lending more value to our quarterly analysis”, explains Chenmeijing Liang, Technology & Market Analyst, Imaging Activities at Yole. And she details Yole’s analysis:
  • Since Q4 2017, “all markets except mobile” have been on a downward slope. At that time, they had reached US$1.5 billion, but are now down to US$1.1 billion, a -26% drop. These markets went through rough times in 2016 for several reasons, but were actually exhibiting high-growth momentum on a multi-annual basis. In fact, the sum of these markets had doubled from Q1 2015, which translates to a +26% CAGR during 2015 – 2017. But then the industry basically lost a full year’s growth – so what is actually happening before Yole’s quarterly-monitoring eyes?
  • Looking closer at the “other” market breakdown, the two largest segments, consumer photography (DSC, DSLR, action cameras, drones) and computing (PC, laptop, tablets), have been on a slippery slope for a long time and are now on par with the other two segments: automotive and security.
  • Q1 2019 and Q2 2019 are notable as the first time that automotive, and then security, became the second-largest CIS segments. This is definitely breaking news, and it will affect the rankings and strategy of the main CIS players. However, this is not all “honor and glory” for the automotive and security markets:
    The downturn in the Chinese and U.S. automotive markets is affecting automotive CIS sales, despite the growing number of cameras per car. While Yole’s initial five-year growth expectation was +19% CAGR for automotive CIS, YoY growth for 2019 is heading towards a -5% to -10% decrease.
  • The same is more or less true for security, which Yole’s analysts originally announced a five-year +19% CAGR expectation for. Unfortunately, YoY growth will likely end up flat in 2019.
  • The largest disappointment is the industrial segment, which had enjoyed a +26% CAGR from 2014 – 2017. But after reaching US$135 million in Q4 2017, it is now back in the US$100 million-per-quarter range. A global halt to capital expenditures in the semiconductor and automotive industries is probably the main reason. On the bright side, positive news from China leads us to the conclusion that this was simply a needed adjustment due to cyclical markets, and that growth could resume in 2020 since the bottom seems to have been reached. Time will tell.