Artificial intelligence-powered newcomers are reshuffling the pack.
Key features of the report
- Intellectual property and silicon business models description and market dynamics
- Image signal processor and vision processor market dynamics
- Technology trends and future outlook
- Descriptions of ecosystem and applications
- Image processing pipeline and deep learning descriptions
Objectives of the report
Provide a clear understanding of the image processor and vision processor technologies and market.
- Ecosystem identification and analysis:
- Determine market dynamics
- Technical market description
- Economic requirements by segment
- Key players by market: analysis
- Market size and market forecast in $M
- Analysis and description of the market and technologies involved:
- Major players on a global basis
- Technology identification for different devices and processes
- Competing technologies
- Main technical challenges
- Future directions
Table of Content
Report objectives and methodology 4
Executive summary 12
Market forecast 67
- Intellectual property market description
- Intellectual property market revenues by player
- Silicon market revenues by player
- IP and silicon market shares
- Intellectual property market revenues per technology
- Silicon market revenues by technology
- Image signal processor and vision processor market description
- Intellectual property market revenues by application
- Silicon market revenues by application
Market and technology trends 80
- Image signal processors in mobile
- Forecast 2012 – 2024 ISP volume shipments in Munits by type of mobile
- Assumptions on average selling price
- Forecast 2012 – 2024 Image signal processors revenues in $M
- AI in mobile devices – Vision processors in mobile devices
- Forecast 2012 – 2024 VP volume shipments in Munits by type of mobile
- Assumptions on average selling price
- Forecast 2012 – 2024 VP revenues in $M
- Vision processing and sensing systems
- Image signal processor
- Forecast 2018 – 2024 ISP volume shipments and number of ISPs per system assumptions
- Forecast 2018 – 2024 ISP revenues in $M and ASP assumptions
- Vision processor dedicated to level 2 and level 3
- Forecast 2018 – 2024 Assumptions for ASP of vision processors
- Forecast 2018 – 2024 VP penetration rate
- Forecast 2018 – 2024 VP volume shipments in Munits by level of autonomy
- Forecast 2018 – 2024 VP revenues in $M by level of autonomy
- Forecast 2018 – 2024 ISP and VP volume shipments in Munits
- Forecast 2018 – 2024 ISP and VP revenues in M$
- Other applications
- Volumes, penetration rate and average selling prices assumptions
- Teardowns – Forecast 2012 – 2024 ISP and VP volume shipments in Munits
- Forecast 2012 – 2024 ISP and VP revenues in $M
- Forecast 2012 – 2024 ISP average selling prices and penetration rates assumptions
- Forecast 2012 – 2024 ISP volume shipment in Munits per application
- Forecast 2012 – 2024 ISP revenues in $M per application
- Forecast 2012 – 2024 VP average selling prices and penetration rates assumptions
- Forecast 2012 – 2024 VP volume shipment in Munits per application
- Forecast 2012 – 2024 VP revenues in $M per application
- Image processing
- Image analysis
Appendix – Yole Développement’s presentation 209
WHAT ARE WE TALKING ABOUT?
The report focuses on describing the markets related to hardware needed for image processing. Behind a camera, there may be several ways to process raw data depending on the purpose. The alternatives usually break down into viewing or analyzing the image to understand the environment around the module or system containing the camera. Each of these purposes, however, requires a different type of hardware.
For visualization, the algorithms needed to transform the raw data into a visible image by the human eye have existed for a long time and are optimized in terms of performance or quality. The hardware has evolved in parallel, and today is embodied in Image Signal Processors (ISPs), allowing processing from the pixels of the image. For analysis, however, new algorithms require computing power to achieve the precision sought in understanding the surrounding environment. That’s especially true for algorithms derived from artificial intelligence techniques such as deep learning. This is where the Vision Processor (VP) comes in. Its goal is to analyze a complete frame, not just the pixel level.
In this report, Yole Développement will segment processing and computing respectively according to their association with the image signal processor and vision processor. At the business level, segmentation is quite simple. Some companies offer a license and royalties for a design, which is known as intellectual property (IP) business. Other companies sell the chips, which we call the silicon business.
WHAT ARE THE MARKET DYNAMICS?
AI has completely disrupted hardware in vision systems, and has had an impact on entire segments, as Mobileye has in automotive, for example. Image analysis adds a lot of value. 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 ISP market offers a steady compound annual growth rate (CAGR) from 2018 to 2024 of 3%, making the total market worth $4.2B in 2024. Meanwhile, the vision processor market is exploding, with a 18% CAGR from 2018 to 2024, making the market worth $14.5B in 2024!
A UNUSUAL ECOSYSTEM HAS BEEN CREATED
Processing and computing hardware for the imaging market has been divided into two different business models. IP companies don’t have physical products, but silicon companies sell the physical processors. The leaders are easy to identify for each category. ARM and Synopsys lead the IP segment and OmniVision, Mobileye and ON Semiconductor lead the silicon segment.
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 mobile device, automotive, computing and surveillance industries. The applications include biometry and photography, autonomous driving, behavioral recognition, human identification and tracking.
It is important to note that historical players have struggled to react to AI’s arrival. That has allowed other companies to get into the business, including smartphone companies like Apple and Huawei, startups like Mobileye, and companies in other segments, like NVIDIA in automotive applications. However, because the trend is towards low-power, low-consumption, always-on computing hardware, the historical players are coming back into the game. AI technologies promise a bright future in many areas, with rapid software and hardware progress. This 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.
Amazon, Altek, Ambarella, Apple, ARM, Bosch, CEVA, Canon, Chips&Media, Continental, Delphi, Denso, GestureTek, Google, Intel, Imagination, Kalray, Mediatek, Intel Mobileye, Intel Movidius, Nec, Nextchip, Nikon, NVIDIA, NXP, Oculus, Omek, OmniVision, ON Semiconductor, Panasonic, Pixelworks, Qualcomm, Quanergy, Samsung, Socionext, Sony, STMicroelectronics, Sunplus, Synopsys, Xilinx, Xperi, and others.
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