Global Image Recognition Market Growth (Status and Outlook) 2023-2029

Global Image Recognition Market Growth (Status and Outlook) 2023-2029

Image recognition, in the context of machine vision, is the ability of software to identify objects, places, people, writing and actions in images. Computers can use machine vision technologies in combination with a camera and artificial intelligence software to achieve image recognition.

LPI (LP Information)' newest research report, the “Image Recognition Industry Forecast” looks at past sales and reviews total world Image Recognition sales in 2022, providing a comprehensive analysis by region and market sector of projected Image Recognition sales for 2023 through 2029. With Image Recognition sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Image Recognition industry.

This Insight Report provides a comprehensive analysis of the global Image Recognition landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyzes the strategies of leading global companies with a focus on Image Recognition portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Image Recognition market.

This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Image Recognition and breaks down the forecast by type, by application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Image Recognition.

The global Image Recognition market size is projected to grow from US$ 20270 million in 2022 to US$ 57920 million in 2029; it is expected to grow at a CAGR of 16.2% from 2023 to 2029.

North America holds the largest share of the global market. Higher adoption of new and advanced technologies such as mobile application security solutions is driving the growth of this regional market. The image recognition market in Asia-Pacific is projected to grow at the highest CAGR during the forecast period. This high growth can be attributed to the high adoption of cloud, mobility, and infrastructure management solutions to address information security.

This report presents a comprehensive overview, market shares, and growth opportunities of Image Recognition market by product type, application, key players and key regions and countries.

Market Segmentation:

Segmentation by type
Code Recognition
Digital Image Processing
Facial Recognition
Object Recognition
Pattern Recognition
Optical Character Recognition

Segmentation by application
BFSI
Media & Entertainment
Retail & Consumer Goods
IT & Telecom
Government
Healthcare
Transportation & Logistics
Others

This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries

The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Qualcomm
NEC
Google
LTU Technologies
Catchoom Technologies
Honeywell
Hitachi
Slyce
Wikitude
Attrasoft

Please note: The report will take approximately 2 business days to prepare and deliver.


*This is a tentative TOC and the final deliverable is subject to change.*
1 Scope of the Report
2 Executive Summary
3 Image Recognition Market Size by Player
4 Image Recognition by Regions
5 Americas
6 APAC
7 Europe
8 Middle East & Africa
9 Market Drivers, Challenges and Trends
10 Global Image Recognition Market Forecast
11 Key Players Analysis
12 Research Findings and Conclusion

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