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Page 1: Embedded Image and Vision Processing 2017 report by Yole Developpement

From Technologies to Market

Embedded Image and Vision Processing

Sample

November 2017

Page 2: Embedded Image and Vision Processing 2017 report by Yole Developpement

2

Biographies and Contacts

ABOUT THE AUTHORS

As a Software & Market Analyst, Dr. Yohann Tschudi is a member of the MEMS & Sensors business unit at Yole Développement(Yole). Yohann is daily working with Yole’s analysts to identify, understand and analyze the role of the software parts within anysemiconductor products, from the machine code to the highest level of algorithms. Market segments especially analyzed byYohann include big data analysis algorithms, deep/machine learning, genetic algorithms, all coming from Artificial Intelligence (IA)technologies.

After his thesis at CERN (Geneva, Switzerland) in particle physics, Yohann developed a dedicated software for fluid mechanicsand thermodynamics applications. Afterwards, he served during 2 years at the University of Miami (FL, United-States) as aresearch scientist in the radiation oncology department. He was involved in cancer auto-detection and characterization projectsusing AI methods based on images from Magnetic Resonance Imaging (MRI). During his research career, Yohann has authored andco-authored more than 10 relevant papers. Yohann has a PhD in High Energy Physics and a master degree in Physical Sciencesfrom Claude Bernard University (Lyon, France).

Email: [email protected]

Yohann Tschudi

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 3: Embedded Image and Vision Processing 2017 report by Yole Developpement

3

TABLE OF CONTENTS

REPORT OBJECTIVES AND METHODOLOGY 5

1 – INTRODUCTION 12

Software

Embedded software

2 – IMAGE PROCESSING 23

Definition

Basics : Primary ISP architecture for Bayer image sensor

Image processing to recover artefacts

Image processing for color reproduction

Image processing with pre-/post-processing

Conclusion

3 – ARTIFICIAL INTELLIGENCE 42

Definition

A modern history of AI

AI technologies

Discussion

4 – PLAYERS AND MARKET DYNAMICS 59

ISP & vision processor

AI in vision systems

CONCLUSIONS 87

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 4: Embedded Image and Vision Processing 2017 report by Yole Developpement

4

Dual cameras

Video stabilization

HDR

Super resolution

Digital zoom

Deep learning

AR/VR

SLAM

Video analytics

3D reconstruction

Forward collision warning

Lane departure

Pedestrian detection

Traffic sign detection

Free space

Gesture recognition

Behavior recognition

Eye tracking

Iris recognition

Face recognition

Face detection

Computational

photography

Machine visionAutomotive

Human machine

interface

SCOPE OF THE REPORT

2 domains are considered in this report

Image signal processor

and vision processor

Artificial intelligence in

vision systems

Technologies

L

e

n

s

Image

sensor

Demosaicin

g

Noise filter

for luma

Color

space

conversion

Noise filter

for chroma

Data

formatter

Gamma

correction

Color

correction

White

balance

Hue

saturation

control

Dead pixel

concealme

nt

Black level

compensati

on

Lens

shading

correction

Edge

enhanceme

nt

Contrast

brightness

control

Not shaded

technologies are not

treated in this report

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 5: Embedded Image and Vision Processing 2017 report by Yole Developpement

5

Algolux, Altek, Ambarella, AMD, ARM, Apple, CEVA, Canon, Chips&Media, DNNresearch, DeepMind, Emotient, Fotonation, Google, Intel, Imagination, Lattice, Microsoft, Mobileye, Movidius, Nextchip, Nvidia, NXP, Omnivision, ON Semiconductors, Pixelworks, Qualcomm, Realface, Socionext, Sony, STMicroelectronics, Sunplus, Synopsys,

Xperi

COMPANIES CITED IN THIS REPORT

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 6: Embedded Image and Vision Processing 2017 report by Yole Developpement

6

SOFTWARE

General definition

Analogy

Set of sequences of instructions (programs) that can be interpreted by a machine and a set of data necessary for these operations

Hardware Software

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 7: Embedded Image and Vision Processing 2017 report by Yole Developpement

7

SOFTWARE LICENSE

Type of licensing for software

Public

domain

Non

protective

FOSS*

license

Protective

FOSS*

license

Proprietary

license

Trade

secret

More rights granted Less rights granted

*Free and Open Source Software

Freeware

Shareware

Freemium

Copyright

retainedNo Yes Yes Yes Yes Yes

Perform and

displayYes Yes Yes Yes Yes No

Copy Yes Yes Yes Often No No

Modify Yes Yes Yes No No No

Distribute YesYes, under same

license

Yes, under same

licenseOften No No

Sublicense Yes Yes No No No No

Examples

SERVER-SIDE

The Google search

algorithm

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 8: Embedded Image and Vision Processing 2017 report by Yole Developpement

8

EMBEDDED SOFTWARE

Global definition

• Embedded software is used to control the limited and set functions of hardware devices. It is not typically workedwith directly by users. Its functions are activated by external controls, either external actions of the device itself orremote input. The device may have communication links to other devices for functionality or in case the deviceneeds to be adjusted, calibrated or diagnosed.

• It is written specifically for the particular hardware that it runs on and usually has processing and memoryconstraints because of the device’s limited computing capabilities. Examples of embedded software include thosefound in dedicated GPS devices, factory robots, some calculators and even modern smartwatches.

• Embedded software varies in complexity as much the devices it is used to control. Although the term is often usedinterchangeably with firmware, embedded software is often the only computer code running on a piece of hardware,while firmware, in contrast, hands over control to an operating system that in turn launches and controls programs.

• In this report we will focus on two types of embedded software in vision systems :

Image processing

Very close to hardware

Inference software from AI’s

technics

High level algorithms

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 9: Embedded Image and Vision Processing 2017 report by Yole Developpement

9

IMAGE PROCESSING PIPELINE

ISP blocks details

L

e

n

s

Image sensor

Demosaicing

Noise filter for

luma

Color space

conversion

Noise filter for

chromaData formatter

Gamma correction Color correctionWhite balance

Hue saturation

control

Dead pixel

concealment

Black level

compensation

Lens shading

correction

Edge enhancementContrast brightness

control

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 10: Embedded Image and Vision Processing 2017 report by Yole Developpement

10

ISP & VISION PROCESSOR MARKET SHARES AND EVOLUTIONS

Some clues on what happening for the hardware segment

IP and hardware

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 11: Embedded Image and Vision Processing 2017 report by Yole Developpement

11

AI IN VISION SYSTEMS

Focus on AI technologies in vision systems

• The main goal of AI is for an artificial system to be autonomous. For that, understanding the environment an navigatethrough it takes a large part of the research.

• Because 80% of the human understanding of the world pass through eyes, vision systems share with AI one mainresearch topic :

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 12: Embedded Image and Vision Processing 2017 report by Yole Developpement

12

DEEP LEARNING

The most powerful method in vision systems

• Deep learning is part of machine learning methods.

• It is based on deep neural networks which are ANN with multiple hidden layers between the input and outputlayers.

• In computer vision, DL is used for object recognition. Although CNNs trained by backpropagation had been aroundfor decades, and GPU implementations of ANNs for years, including CNNs, fast implementations of CNNs withmax-pooling on GPUs and high level memory were needed to progress on computer vision.

Example of DNN used

for face recognition

during the training phase

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 13: Embedded Image and Vision Processing 2017 report by Yole Developpement

13

AI RELATED TO VISION SYSTEMS GLOBAL CHARACTERISTICS

Main characteristics of the embedded inference software technologies in vision systems

High

Medium

Low

Not relevant

Image

processing

Face

detectionEye tracking

Iris

recognition

Face

recognition

Object

detection

Free space

recognition

Gesture

recognition

Object

recognition

Behavior

recognition

CPU

requirements

Memory

requirements

Resolution

requirements

Execution

speed

requirements

Algorithm

complexity

Training

requirements

Range <10m <1m <1m <1m <100m <3m <3m <50m 5-20m

Learn in usage Yes Yes No Yes No No No No No

Input from

Photo (P) or

Video (V)

P/V P V P P V V V V V

Very high

Object analysis Scene analysis

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 14: Embedded Image and Vision Processing 2017 report by Yole Developpement

14

EMERGENCE OF AI – TECHNOLOGICAL FACTORS

Technological factors implied in the emergence of AI in vision systems and forecast

©2017 | www.yole.fr | Embedded software in vision systems | Sample

Page 16: Embedded Image and Vision Processing 2017 report by Yole Developpement

Vision systems are becoming increasingly important. Therefore, this report shows and explains the close links between embedded software and hardware in vision systems at the technology and market levels. What are the software technologies? How do they impact the hardware? Which hardware is impacted? What kinds of markets are affected? And how will they evolve?

We can consider software in vision systems as having two different levels. The first is very close to the hardware, inscribed inside standalone field programmable gate array (FPGA) or application specific integrated circuit (ASIC) chips, or integrated into more complicated architectures. This layer, not often considered, is the most important step in any image treatment after image acquisition by pixels. Image processing, realized in the image signal processor (ISP), has a quite simple function. It must transform a signal from the sensor to an understandable image for the human eye. It is composed as a pipeline of multiple blocks, where each block takes as input the output of the previous block. A lot

of different algorithms are implemented to accomplish tasks such as removing artefacts, color correction and reproduction. This is done at a single-pixel or pixel-group level and does not need a lot of memory or power.

The second software layer is completely different, with much more diverse and complicated functions. In this report, we focused on embedded software and, more precisely, inference software derived from the latest artificial intelligence (AI) methods. This kind of technology necessitates a lot of memory and computing power. It uses complete image frames as input, and its goal is not to correct, but to analyze and understand the world in the picture. In vision systems, AI technology focuses on detection of eyes, faces, traffic signs, pedestrians, lanes, objects in front of cars and free space, and recognition of faces, irises, behaviors and gestures based on a mathematical technique called a neural network. This report especially investigates one of the most famous technologies, which has given spectacular results in recent years: deep learning.

EMBEDDED IMAGE AND VISION PROCESSING Market & Technology report - November 2017

SOFTWARE IN VISION SYSTEMS

From algorithms included in the image processing pipeline to neural networks running in vision processors, focus on the evolution of hardware in vision systems and how software disrupts this domain.

KEY FEATURES OF THE REPORT Get the sample of the report on www.i-Micronews.com• Image processing technology

description• Description of Artificial Intelligence

(AI) technology in vision systems• Intellectual property, hardware

and business models for the image signal processor and vision processor market

• AI technology and business models in the vision system ecosystem

• Technology trends and future outlook

(Yole Développement, November 2017)

Artificial intelligence technologies in vision systems

Computational photography

Machine vision Automotive

Human machine interface

Dualcameras Video

stabilization

HDR

Superresolution

Digitalzoom

Deeplearning

AR/VR

SLAM

Videoanalytics 3D

reconstruction

Forwardcollisionwarning

Lanedeparture

Pedestriandetection

Traffic signdetection

Free space

Gesturerecognition

Behaviorrecognition

Irisrecognition

Facerecognition

Facedetection

OBJECTIVES OF THE REPORTUnderstand the technologies• Image processing pipeline• AI technologies based on neural

networks

Understand the evolution of hardware • Business models• Image signal processor to vision

processors to sensor fusion• Market share and evolution

Understand how software is disrupting hardware and future trends

The shaded technologies are addressed in this report

Page 17: Embedded Image and Vision Processing 2017 report by Yole Developpement

EMBEDDED IMAGE AND VISION PROCESSING

HARDWARE MARKET AND BUSINESS MODELS

AI has completely disrupted hardware in vision systems, and has had an impact on entire segments, like Mobileye has in automotive, for example. Image analysis adds a lot of value and

image sensor builders are therefore increasingly interested in integrating a software layer to their system in order to capture it. Today, image sensors must go beyond taking images – they must be able to analyze them.

However, to run these types of software, high power computing and memory are necessary, which led to the creation and development of vision processors. The image signal processor (ISP) market offers a steady compound annual growth rate (CAGR) of 6.3%, making the total market worth $4,400M in 2017. Meanwhile, the vision processor market is exploding, with a 30.7% CAGR and a market worth $653M in 2017!

Today, optimization requires software and hardware to be developed in parallel. Depending on the issues and specifications, companies can invest more in hardware than software or vice versa. However, software is easier to specify, tune and update, and so its growth is more important than hardware. The AI market is therefore expected to reach $35B in 2025 with an estimated CAGR at 50% per year from 2017-2025.

This report carefully evaluates ISP and vision processor market shares and their evolution in order to correctly understand how AI technology impacts the hardware. This market has been divided in two different business models: Intellectual Property (IP) companies, which don’t have physical products, and hardware companies, which sell the processors physically. The leaders are pretty easy to identify for each category. ARM and Synopsys lead the IP segment and Omnivision, Mobileye and ON Semiconductor lead the hardware segment.

The AI market, particularly in vision systems, is new and still moving, with hundreds of startups created each year. It has no clear leaders but a lot of highly specialized companies. This report therefore gives a high-level view of driving forces, technology hype, and the most important mergers and acquisitions.

The main goal of this report is to understand what is happening with the emergence of AI. Even if it is not a new technology, thanks to technological factors AI has made a spectacular entry into vision systems. It opens new perspectives in various segments such as automotive, surveillance, biometrics and medical. However, it also poses ethical questions, which we have tried to answer.

AI technologies promise a bright future in many areas, with rapid software and hardware progress. In autonomous vehicles, AI allows cars to understand the world around them, predict trajectories, communicate and drive. This has led to the development of sensor fusion boards. For example, NVidia’s Drive PX boards provide very high performance computing and memory, giving the ability to compile information from many completely different sensors. In surveillance and security, face and iris recognition have never been as powerful, entering the consumer world through the iPhone X this year, and behavior recognition is on track.

From image signal processor to sensor fusion processor

Hardware markets size evolution 2012-2021

(Yole Développement, November 2017)

(Yole Développement, November 2017)

Vision processor from Mobileye

Frame processing

Vision processor

Amount of data processed

Fully AI to reach autonomy Introduction of AI

algorithms

Is part of

Price per unit

> $1000

$10

< $1

Set of pixels processing

ISP

Image processing algorithms

Standalone ISP from Altek

Frame processing + other sensors

Sensor fusion processor

Sensor fusion processor from NVidia

$

sion processor r

Sensor fusion processor from NVidia

WHEN SOFTWARE DISRUPTS HARDWARE

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Rev

enue

s (U

S$ m

illio

n)

Intellectual Property - Image signal processor Intellectual Property - Vision processor Hardware - Vision processor Hardware - Image signal processor

Page 18: Embedded Image and Vision Processing 2017 report by Yole Developpement

MARKET & TECHNOLOGY REPORT

Emergence of artificial intelligence - Technological factors

(Yole Développement, November 2017)

Find more details about

this report here:

COMPANIES CITED IN THE REPORT (non exhaustive list)Algolux, Amazon, Altek, Ambarella, AMD, ARM, Apple, B-Secur, Biowatch, CEVA, Canon, Chips&Media, Cognitec, Delta ID, Ergoneers, EyeLink, Eyesmart Technology, Eyetech, Face++, Facebook, Fotonation, Google, IBM, Intel, Imagination, Irisys, Iritech, ISCAN, Kairos, LC Technologies, LG, Microsoft, Mobbeel, Mobileye, Movidius, Nec, Nextchip, Nvidia, NXP, Omnivision, ON Semiconductor, OpenCV, Parrot, Pixelworks, Princeton Identity, Qualcomm, SensorMotoric Instruments, Smart Eye, Socionext, Sony, Sthaler, STMicroelectronics, Sunplus, Synopsys, The Eye Tribe, Tobii, Xperi...And more.

Report objectives and methodology 5

Introduction 12

> Software> Embedded software

Image processing 23

> Definition> Basics : Primary ISP architecture for

Bayer image sensor> Image processing to recover artefacts> Image processing for color reproduction> Image processing with pre-/post-

processing

> Conclusion

Artificial intelligence 41

> Definition

> A modern history of AI

> AI technologies

> Discussion

Players and market dynamics 59

> ISP and vision processor

> AI in vision systems

Conclusions 83

Company profile 90

TABLE OF CONTENTS (complete content on i-Micronews.com)

• 3D TSV and 2.5D Business Update - Market and Technology Trends 2017

• 3D Imaging and Sensing 2017 • Status of the CMOS Image Sensor Industry

2017

RELATED REPORTSBenefit from our Bundle & Annual Subscription offers and access our analyses at the best available price and with great advantages

AUTHORDr. Yohann Tschudi as a Software & Market Analyst , Dr. Yohann Tschudi is a member of the MEMS & Sensors business unit at Yole Développement (Yole). Yo-hann is daily working with Yole’s analysts to identify, understand and analyze the role of the sof tware par ts within any semiconductor products, from the ma-chine code to the highest level of algo-rithms. Market segments especially ana-lyzed by Yohann include big data analysis algorithms, deep/machine learning, ge-netic algorithms, all coming from Ar tif i-cial Intelligence (IA) technologies.After his thesis at CERN (Geneva, Swit-zerland) in par ticle physics, Yohann de-veloped a dedicated software for f luid mechanics and thermodynamics appli-cations. Afterwards, he served during 2 years at the University of Miami (FL, United-States) as a research scientist in the radiation oncology depar tment. He was involved in cancer auto-detection and characterization projects using AI methods based on images from Magne-tic Resonance Imaging (MRI). During his research career, Yohann has authored and co-authored more than 10 relevant papers. Yohann has a PhD in High Energy Physics and a master degree in Physical Sciences from Claude Bernard University (Lyon, France).

Find all our reports on www.i-micronews.com

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

2008 2010 2012 2014 2016 2018 2020

Amount of data stored

$0,01

$1

$100

$10 000

$1 000 000

$100 000 000

$10 000 000 000

$1 000 000 000 000

1950 1960 1970 1980 1990 2000 2010 2020

IBM 7030 Stretch

Cray X-MP/48

Beowulf cluster

KASY0

Approximate cost per GFLOPS(109 operations per second)

(Exabytes – 1018 bytes)

Estimated

Al is very exciting for the entire area of vision systems. This report tries to show why it is important to understand the technologies and their impacts, and how to react. AI is in vision systems, from technology to market.

Page 19: Embedded Image and Vision Processing 2017 report by Yole Developpement

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OUR 2017 REPORTS PLANNING (1/2)

MARKET AND TECHNOLOGY REPORTS by Yole Développement

o MEMS & SENSORS

− Acoustic MEMS and Audio Solutions 2017

− 3D Imaging & Sensing 2017

− Microspectrometers Markets and Applications 2017

− Status of the MEMS Industry 2017*

− MEMS & Sensors for Automotive 2017

− High End Inertial Sensors for Defense and Industrial Applications 2017*

− Magnetic Sensors Market and Technologies 2017

− Sensors and Sensing Modules for Smart Homes and Buildings 2017

− Sensing and Display for AR/VR/MR 2017

− MEMS Packaging 2017

− Fingerprint Sensor Applications and Technologies - Consumer Market Focus 2017

o RF DEVICES AND TECHNOLOGIES

− RF Front End Modules and Components for Cellphones 2017

− Advanced RF SiP for Cellphones 2017

− 5G and Beyond (Vol 1): Impact on RF Industry, from Infrastructure to Terminals

2017

− 5G and Beyond (Vol 2): RF Materials Platform, from Infrastructure to Terminals

2017

− RF Technologies for Automotive Applications 2017

− GaN and Si LDMOS Market and Technology Trends for RF Power 2017

o MANUFACTURING

− Glass Substrate Manufacturing 2017

− Equipment & Materials for Fan Out Technology 2017

− Equipment and Materials for 3D TSV Applications 2017

− Emerging Non Volatile Memories 2017*

o MEDTECH

− Status of the Microfluidics Industry 2017

− Solid State Medical Imaging 2017

− Connected Medical Devices: the Internet of Medical Things 2017

− Sensors for Medical Robotics 2017

− Artificial Organs: Market & Technology Analysis 2017

− Organs-on-a Chip 2017

o ADVANCED PACKAGING

− Advanced Substrates Overview 2017

− Status of the Advanced Packaging Industry 2017

− Fan Out Packaging: Market & Technology Trends 2017*

− 3D Business Update: Market & Technology Trends 2017*

− Advanced QFN: Market & Technology Trends 2017**

− Inspection and Metrology for Advanced Packaging Platform 2017**

− MEMS Packaging 2017

− Advanced Packaging for Memories 2017

− Advanced RF SiP for Cellphones 2017

− Power Packaging Market and Technology Trends 2017

− Embedded Die Packaging: Technologies and Markets Trends 2017

o IMAGING & OPTOELECTRONICS

− 3D Imaging & Sensing 2017

− Status of the CMOS Image Sensor Industry 2017*

− Camera Module for Consumer and Automotive Applications 2017*

− Uncooled Infrared Imaging Technology & Market Trends 2017*

− Solid State Medical Imaging 2017

o BATTERY AND ENERGY MANAGEMENT

− Status of Battery Industry for Stationary, Automotive and Consumer Applications

*2016 version still available / **To be confirmed

Page 30: Embedded Image and Vision Processing 2017 report by Yole Developpement

26©2017 | www.yole.fr | About Yole Développement

OUR 2017 REPORTS PLANNING (2/2)o POWER ELECTRONICS

− Status of Power Electronics Industry 2017*

− Silicon Power Mosfet: Market and Technology Trends 2017

− IGBT Market and Technology Trends 2017

− Power Packaging Market and Technology Trends 2017

− Power SiC 2017: Materials, Devices, and Applications*

− Power GaN 2017: Materials, Devices, and Applications*

− Materials Market Opportunities for Cellphone Thermal Management (Battery

Cooling, Fast Charging, Data Processing, Battery Cooling, etc.) 2017

− Gate Driver Market and Technology Trends 2017

− Power Management ICs Market Quarterly Update 2017

− Power Electronics for Electrical Aircraft, Rail and Buses 2017**

− Thermal Management for LED and Power 2017

o COMPOUND SEMICONDUCTORS

− Power SiC 2017: Materials, Devices, and Applications*

− Power GaN 2017: Materials, Devices, and Applications*

− GaN and Si LDMOS Market and Technology Trends for RF Power 2017

− 5G and Beyond (Vol 2): RF Materials Platform, from Infrastructure to Terminals

2017

− Bulk GaN Substrate Market 2017

o DISPLAYS

− MicroLED Displays 2017

− Display for Augmented Reality, Virtual Reality and Mixed Reality 2017

− Quantum Dots for Display Applications 2017

− Phosphors & Quantum Dots 2017 - LED Downconverters for Lighting & Displays

− Organic Thin Film Transistor 2016: Flexible Displays and Other Applications

− Automotive Lighting 2017 - Technology, Industry and Market Trends

o SOLID STATE LIGHTING

− UV LEDs 2017 - Technology, Manufacturing and Application Trends*

− Horticultural Lighting 2017 - Technology, Industry and Market Trends

− Automotive Lighting 2017 - Technology, Industry and Market Trends*

− Active Imaging and Lidar 2017 (Vol 2) - IR Lighting**

− LED Lighting Module 2017 - Technology, Industry and Market Trends

− IR LEDs and Lasers - Technology Applications and Industry Trends 2017

− Phosphors & Quantum Dots 2017 - LED Downconverters for Lighting & Displays

− MicroLED Displays 2017

− CSP LED Lighting Module 2017

− LED Packaging 2017

− Thermal Management for LED and Power 2017

PATENT ANALYSIS by Knowmade

− Consumer Physics SCiO Molecular Sensor Patent-to-Product Mapping 2017

− Patent Licensing Companies in the Semiconductor Market - Patent Litigation

− Risk and Potential Targets 2017

− MEMS Microphone: Patent Landscape Analysis 2017

− MEMS Microphone: Knowles’ Patent Portfolio Analysis 2017

− Microbolometer: Patents Used in Products 2017

− Microfluidic Technologies for Diagnostic Applications Patent Landscape 2017

− Micropumps: Patent Landscape Analysis 2017

− GaN Technology: Top-100 IP Profiles 2017

− MicroLEDs: Patent Landscape Analysis 2017

− Consumer Physics SCiO Molecular Sensor Patent-to-Product Mapping 2017

− Uncooled Infrared Imaging: Patent Landscape Analysis 2017

− 3D Monolithic Memory: Patent Landscape Analysis 2017

TEARDOWN & REVERSE COSTING by System Plus Consulting More than 60 teardowns and reverse costing analysis and cost simulation tools to be

published in 2017.*2016 version still available / **To be confirmed

Page 31: Embedded Image and Vision Processing 2017 report by Yole Developpement

27©2017 | www.yole.fr | About Yole Développement

OUR 2016 PUBLISHED REPORTS LIST (1/2)

MARKET AND TECHNOLOGY REPORTS by Yole Développement

o MEMS & SENSORS

− Gas Sensors Technology and Market 2016

− Status of the MEMs Industry 2016

− Sensors for Cellphones and Tablets 2016

− Market and Technology Trends of Inkjet Printheads 2016

− Sensors for Biometry and Recognition 2016

− Silicon Photonics 2016

o IMAGING & OPTOELECTRONICS

− Status of the CMOS Image Sensor Industry 2016

− Uncooled Infrared Imaging Technology & Market Trends 2016

− Imaging Technologies for Automotive 2016

− Sensors for Drones & Robots: Market Opportunities and Technology Evolution 2016

o MEDTECH

− BioMEMS 2016

− Point of Care Testing 2016: Application of Microfluidic Technologies

o ADVANCED PACKAGING

− Embedded Die Packaging: Technology and Market Trends 2017

− 2.5D & 3D IC TSV Interconnect for Advanced Packaging: Business Update 2016

− Fan-Out: Technologies and Market Trends 2016

− Fan-In Packaging: Business update 2016

− Status and Prospects for the Advanced Packaging Industry in China 2016

o MANUFACTURING

− Thin Wafer Processing and Dicing Equipment Market 2016

− Emerging Non Volatile Memories 2016

o COMPOUND SEMICONDUCTORS

− Power GaN 2016: Epitaxy and Devices, Applications and Technology Trends

− GaN RF Devices Market: Applications, Players, Technology and substrates 2016

− Sapphire Applications & Market 2016: from LED to Consumer Electronics

− Power SiC 2016: Materials, Devices, Modules, and Applications

o LED

− UV LED Technology, Manufacturing and Applications Trends 2016

− OLED for Lighting 2016 – Technology, Industry and Market Trends

− Automotive Lighting: Technology, Industry and Market Trends 2016

− Thermal Management Technology and Market Perspectives in Power Electronics and

LEDs 2017

− Organic Thin Film Transistor 2016: Flexible Displays and Other Applications

− Sapphire Applications & Market 2016: from LED to Consumer Electronics

− LED Packaging 2017: Market, Technology and Industry Landscape

o POWER ELECTRONICS

− Power Electronics for EV/HEV 2016: Market, Innovations and Trends

− Status of Power Electronics Industry 2016

− Passive Components Technologies and Market Trends for Power Electronics 2016

− Power SiC 2016: Materials, Devices, Modules, and Applications

− Power GaN 2016: Epitaxy and Devices, Applications, and Technology Trends

− Inverter Technologies Trends & Market Expectations 2016

− Opportunities for Power Electronics in Renewable Electricity Generation 2016

− Thermal Management Technology and Market Perspectives in Power Electronics and

LEDs 2017

− GaN RF Devices Market: Applications, Players, Technology and substrates 2016

o BATTERY AND ENERGY MANAGEMENT

− Beyond Li-ion Batteries: Present and Future Li-ion Technology Challengers 2016

− Stationary Storage and Automotive Li-ion Battery Packs 2016

− Opportunities for Power Electronics in Renewable Electricity Generation 2016

Page 32: Embedded Image and Vision Processing 2017 report by Yole Developpement

28©2017 | www.yole.fr | About Yole Développement

OUR 2016 PUBLISHED REPORTS LIST (2/2)

PATENT ANALYSIS by Knowmade

− Microbattery Patent Landscape Analysis

− Miniaturized Gas Sensors Patent Landscape Analysis

− 3D Cell Culture Technologies Patent Landscape

− Phosphors and QDs for LED Applications Patent Landscape

− TSV Stacked Memory Patent Landscape

− Fan-Out Wafer Level Packaging Patent Landscape Analysis

TEARDOWN & REVERSE COSTING by System Plus Consulting More than 45 teardowns and reverse costing analysis and cost simulation tools published

in 2016.

MORE INFORMATION

o All the published reports from the Yole Group of Companies are available on our website

www.i-Micronews.com.

o Ask for our Bundle and Annual Subscription offers: With our bundle offer, you choose the

number of reports you are interested in and select the related offer. You then have up to 12

months to select the required reports from the Yole Développement, System Plus Consulting

and KnowMade offering. Pay once and receive the reports automatically (multi-user format).

Contact your sales team according to your location (see the last slide).

Page 33: Embedded Image and Vision Processing 2017 report by Yole Developpement

29©2017 | www.yole.fr | About Yole Développement

MICRONEWS MEDIA

o About Micronews Media

To meet the growing demand for market,

technological and business information,

Micronews Media integrates several tools able

to reach each individual contact within its

network.We will ensure you benefit from this.

ONLINE ONSITE INPERSON

@Micronews e-newsletter

i-Micronews.com

i-Micronewsjp.com

FreeFullPDF.com

Events Webcasts

Unique, cost-effective ways

to reach global audiences.

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Seven main events planned for

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Contacts: Camille Veyrier ([email protected]) and Clotilde Fabre ([email protected]), Marketing & Communication Project Managers.

Page 34: Embedded Image and Vision Processing 2017 report by Yole Developpement

30©2017 | www.yole.fr | About Yole Développement

CONTACT INFORMATION

o CONSULTING AND SPECIFIC ANALYSIS

• North America: Steve LaFerriere, Director of Northern America Business DevelopmentEmail: [email protected] – +1 31 06 008 267

• Japan & Rest of Asia: Takashi Onozawa, General Manager, Asia Business DevelopmentEmail: [email protected] - +81 3 4405 9204

• Greater China: Mavis Wang, Director of Greater China Business DevelopmentEmail: [email protected] - +886 979 336 809

• RoW: Jean-Christophe Eloy, CEO & President, Yole DéveloppementEmail [email protected] - +33 4 72 83 01 80

o REPORT BUSINESS

• North America: Steve LaFerriere, Director of Northern America Business DevelopmentEmail: [email protected] – +1 31 06 008 267

• Europe: Lizzie Levenez, EMEA Business Development ManagerEmail: [email protected] - +49 15 123 544 182

• Rest of Asia: Takashi Onozawa, General Manager, Asia Business DevelopmentEmail: [email protected] - +81 3 4405 9204

• Japan & Asia: Miho Othake, Account ManagerEmail: [email protected] - +81 3 4405 9204

• Greater China: Mavis Wang, Director of Greater China Business DevelopmentEmail: [email protected] - +886 979 336 809

o FINANCIAL SERVICES

• Jean-Christophe Eloy, CEO & PresidentEmail: [email protected] - +33 4 72 83 01 80

o GENERAL

• Public Relations: [email protected] - +33 4 72 83 01 89

• Email: [email protected] - +33 4 72 83 01 80

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