The global image recognition market is predicted to reach USD 92.60 billion in 2024 and USD 225.66 billion by 2029, growing at an annual development rate of 19.5% over the outlook period.
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 cameras 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, and guiding autonomous robots and cars. Autonomous 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 USD 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.
Images are real and large, and unlike other forms of data, they also cannot be easily falsified. These characteristics make images and big data repositories, and therefore, the exploitation of such precious data an excellent source of information for banks and financial institutions. The BFSI industry has been a great benefactor of artificial intelligence, with companies in this industry relying on technology for various applications like staying competitive in an ever-changing market, personalizing communication, and improving productivity by automating monotonous tasks.
Facebook can now correctly identify and attribute 98% of your images to the right person. Imaging technology is used to identify and remove bogus social accounts. Such identification based on false images has immense potential to enrich banks' credit rating and risk modeling. The images could also be used by insurers in assessing risks and identifying fraud. As image processing and recognition become major applications of AI in various sectors, it should experience positive growth over the forecast period.
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.
The cost of manufacturing image recognition systems is very high, and the return on investment in physical assets is low. 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.
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REPORT METRIC |
DETAILS |
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Market Size Available |
2023 to 2029 |
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Base Year |
2023 |
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Forecast Period |
2024 to 2029 |
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CAGR |
19.5% |
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Segments Covered |
By Technique, Application, Component, Deployment, Vertical, and Region |
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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 |
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Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
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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. |
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 into media and entertainment, BFSI, automotive and transportation, retail and e-commerce, telecommunications and computing, government, healthcare, and others.
North America accounted for the largest share in global image recognition market, 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.
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).
By Technique
By Application
By Component
By Deployment Mode
By Vertical
By Region
Frequently Asked Questions
Major applications include security and surveillance, healthcare, automotive, retail, and e-commerce. In healthcare, image recognition is used for diagnostics and medical imaging. In retail, it enhances customer experience through visual search and inventory management. Automotive applications include driver assistance systems and autonomous vehicles.
Artificial intelligence, particularly machine learning and deep learning, significantly enhances image recognition capabilities by improving accuracy and efficiency. AI algorithms enable systems to learn from vast datasets, recognizing patterns and objects with minimal human intervention, thus expanding the applications and effectiveness of image recognition technologies.
Government regulations play a significant role, particularly concerning data privacy and security. Regulations like the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States impose stringent requirements on how image data is collected, stored, and used, impacting market operations and development.
Future trends include the integration of image recognition with augmented reality (AR) and virtual reality (VR), increasing use in smart cities for surveillance and infrastructure management, advancements in facial recognition technology, and growing applications in the automotive sector for enhanced driver assistance systems and autonomous driving. Enhanced computational power and AI advancements will further drive innovation and market growth.
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