The global image recognition market is anticipated to develop from $ 38.0 billion in 2019 to $ 52.9 billion in 2025, at an annual development rate of 19.5% over the outlook period of 2020 to 2025.
Image recognition plays a crucial role in identifying different features like places, objects, people, and actions in images. Computers implement these machine vision technologies with the help of camera and artificial intelligence to achieve image recognition. This technique is used to perform a large number of machine-based visual tasks, such as tagging image content with META tags, searching for image content, guiding autonomous robots and cars. autonomous, and systems to prevent accidents.
The adoption of artificial intelligence (AI) technology is increasing due to its ability to improve and automate operations and enhance the user experience. Governments are also focusing on increasing their artificial intelligence capabilities to revolutionize various sectors, from healthcare to transportation. The EU has pledged to invest €1.5 billion in artificial intelligence to catch up with the United States and Asia.
As AI becomes the heart of many technological applications, investments in the sector are increasing. Image recognition is one of the standard features of many AI applications. Therefore, the market is expected to take advantage of fast growing technology and develop in the coming years.
Recent Developments:
Market Growth and Trends:
Drivers and Market Restraints:
Driver: Increasing use of image recognition applications
Smartphones and camera devices are attracting sellers to invest in the image recognition market. New mobile apps allow online shoppers to find the product they want just by taking a photo. The image is loaded into an application that suggests elements that are the same or have similar attributes and even substitutes. Image recognition has the potential to turn an image into a hyperlink, information, coupon, and video. These recognition technologies help consumers instantly collect product information by taking a photo on their mobile device. The advent of new applications like games, price comparison, video search, e-commerce, interactive television, augmented reality (AR), image recognition, shelf recognition and many more are helping consumers. Consumers instantly collect information from 40 to 50 products on the shelves at the same time just by taking a photo with image recognition technology.
Restraint : High cost of installing image recognition systems
The cost of manufacturing image recognition systems is very high and the return on investment is low in physical assets. This factor is a major obstacle to the growth of the global image recognition market, as most technologies such as Business Intelligence (BI), knowledge management, customer relationship management (CRM), customer recognition and enterprise resource planning (ERP) have a huge development cost.
REPORT METRIC |
DETAILS |
Market Size Available |
2020 – 2026 |
Base Year |
2020 |
Forecast Period |
2022 - 2027 |
CAGR |
19.5% |
Segments Covered |
By Technique, Application, Component, Deployment, Vertical, and Region |
Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
Market Leaders Profiled |
Qualcomm Technologies, Inc. (United States), NEC Corporation (Japan), Google (United States), LTU Technologies (France), Catchoom Technologies SL (Spain), Honeywell International Inc (United States), Hitachi, Ltd. (Japan), Slyce (Canada), Wikitude GmbH (Austria), Attrasoft, Inc (United States), AWS (United States), Microsoft (United States), IBM (United States United States), Blippar (United States) Uni), Planorama (France), Ricoh Innovations Corporation (United States), Pattern Recognition Company GMBH (Germany), Trax Retail (Singapore), Intelligent Retail (Russia) and Snap2Insight Inc (United States) and Others. |
Global Image Recognition Market Segmentation:
the global image recognition system market has been segmented into object recognition, QR/barcode recognition, pattern recognition, facial recognition, and optical character recognition.
the market has been segmented into imaging and digitization, security and surveillance, augmented reality, marketing and advertising, and image search.
the image recognition market has been segmented into hardware, software, and service. The services segment is expected to experience a remarkable growth rate during the forecast period. The software segment had a significant market share in 2019 due to the increasing adoption of image processing software for various applications such as medical imaging, computer graphics, and photo editing.
the market has been segmented on-premises and in the cloud.
the market was segmented in media and entertainment, BFSI, automotive and transportation, retail and e-commerce, telecommunications and computing, government, healthcare, and others.
Regional Analysis:
North America accounted for the largest share in the global image recognition in 2019, primarily due to the rapid growth of cloud-based streaming services in the US. The growth of the segment is attributed to the increasing integration of artificial intelligence computing platforms and mobiles in the field of digital shopping and electronic commerce. The European regional market is expected to experience significant growth during the forecast period due to increasing advances in automotive obstacle detection technologies in the area.
Key players in the market:
The main players in the image recognition market presented in this report are Qualcomm Technologies, Inc. (United States), NEC Corporation (Japan), Google (United States), LTU Technologies (France), Catchoom Technologies SL (Spain), Honeywell International Inc (United States), Hitachi, Ltd. (Japan), Slyce (Canada), Wikitude GmbH (Austria), Attrasoft, Inc (United States), AWS (United States), Microsoft (United States), IBM (United States United States), Blippar (United States) Uni), Planorama (France), Ricoh Innovations Corporation (United States), Pattern Recognition Company GMBH (Germany), Trax Retail (Singapore), Intelligent Retail (Russia) and Snap2Insight Inc (United States).
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