市场调查报告书
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1518791
全球人工智慧影像辨识市场2024-2031Global AI in Image Recognition Market 2024-2031 |
影像辨识市场中的人工智慧 (AI) 预计在预测期内(2024-2031 年)复合年增长率将达到 15.3%。人工智慧技术的不断发展推动了全球人工智慧图像辨识市场的成长。深度学习模型使电脑视觉、机器学习和人工智慧的发展成为可能,深度学习模型使影像辨识系统透过接触全球大型资料集而不断变得更好。根据资讯系统审计与控制协会的数据,2022 年12 月,脸部影像辨识市场规模预计到2028 年将达到126.7 亿美元,高于2021 年的50.1 亿美元。的需求推动的使用该技术协助刑事调查、进行监视或从事其他与安全相关的活动。
市场动态
Global AI in Image Recognition Market Size, Share & Trends Analysis Report by Offering (Hardware, Software, and Service), by Technology (QR/Barcode, Digital Image Processing Facial Recognition, Object Recognition, Pattern Recognition, and Optical Character Recognition), and by Vertical Industry (BFSI, Retail & E-Commerce, Media & Entertainment, Healthcare, Government, Automotive, Telecommunication, Manufacturing, and Other) Forecast Period (2024-2031)
Artificial Intelligence (AI) in image recognition market is anticipated to grow at a significant CAGR of 15.3% during the forecast period (2024-2031). The ongoing developments in AI technology have driven the growth of the global AI in image recognition market. The developments in computer vision, machine learning, and artificial intelligence are made possible by deep learning models, which allow image recognition systems to continuously get better by being exposed to large datasets globally. According to the Information Systems Audit and Control Association, in December 2022, the facial image recognition market size is forecasted to reach $12.67 billion by 2028, up from $5.01 billion in 2021. This increase is also driven by growing demand from governments and law enforcement agencies that use the technology to assist in criminal investigations, conduct surveillance, or engage in other security-related activities.
Market Dynamics
Increasing Adoption of Real-Time Image Recognition
Real-time image recognition uses models and algorithms that are intended to recognize and classify photos according to the items and patterns they include. Image recognition enables computers to interpret images in ways that are similar to human vision by translating them into numerical or symbolic information. Additionally, computer vision that is used to recognize or detect an image or an attribute in digital photos or videos-heavily depends on automated image recognition systems. Users can collect and evaluate data in real-time with its help. High-dimensional data is gathered, and it yields information that can be numerical or symbolic. Computer vision includes object recognition, event detection, image reconstruction, learning, and video tracking under the umbrella of image recognition. The increasing demand for real-time image recognition tools across end-user verticals is a key factor driving the global market growth.
AI for Fraud Detection, Transaction Screening and Monitoring
Using image recognition software, risk models, and other AI-based techniques, in particular, institutions can use AI to recognize abnormal transactions and identify suspicious and potentially fraudulent activity (such as fraudulent use of customers' personal information, misrepresenting products/services, and other frauds). AI can also increase customer satisfaction by lowering the frequency of false positives, or the rejection of otherwise legitimate transactions (such as a credit card payment that is mistakenly refused). By automating data analysis, enhancing risk assessment, identifying intricate patterns, and lowering false positives, AI improves AML compliance and screening. Examining a variety of data points, such as transaction history, geographic location, and behavioral trends, can assist in determining the risk profile of clients.
Market Segmentation
Services are Projected to Hold the Largest Segment
The services segment is expected to hold the largest share of the market. The primary factors supporting the growth include the increasing demand for specialized image recognition systems that may be adjusted to match the unique requirements of companies in a range of sectors. With this degree of customization, businesses can easily incorporate image recognition technology into their current workflows and systems, increasing productivity and efficiency. The market player offers AI-driven service, and it contributes to shorter rollout times when launching operations while ensuring privacy, reducing introductory costs, and minimizing complications. For instance, in April 2024, Sony Semiconductor Solutions Corp. introduced and began operating an edge AI-driven vision detection solution at 500 convenience store locations in Japan to improve the benefits of in-store advertising. This solution was developed with Console Enterprise Edition, one of the services offered by AITRIOS, and is installed on the partner's Microsoft Azure cloud infrastructure.
Retail & E-Commerce Segment to Hold a Considerable Market Share
The factors supporting segment growth include the growing adoption of image identification by online users to look for clothes or accessories by snapping a photo of a desired color, texture, print, or article of apparel. Market players are turning to AI to better predict shopper demands. Smarter retail is the next generation of user experiences for customers, consumers, and point-of-sell organizations. For instance, in January 2024, Lenovo featured AI-powered, end-to-end retail solutions designed to support smarter, safer, and more secure experiences for retailers and shoppers across any category.
Global AI in image recognition market is further segmented based on geography including North America (the US, and Canada), Europe (the UK, Italy, Spain, Germany, France, and the Rest of Europe), Asia-Pacific (India, China, Japan, South Korea, and Rest of Asia-Pacific), and the Rest of the World (the Middle East & Africa, and Latin America).
Growing Adoption of AI in Image Recognition in Asia-Pacific
The regional growth is attributed to pivotal factors such as the increasing usage of tablets and smartphones, the speed at which technology is developing, the acceptance of image recognition in countries such as China, Japan, South Korea, and India, and the increasing adoption of facial recognition in security and surveillance systems. Market players in the region offer AI facial recognition modules with a variety of application scenarios, including facial recognition vending machines, smart access controls, smart door locks, and elevator control systems. For instance, in April 2021, Canaan announced a partnership with Cathay to introduce the AI facial recognition module and AI chip in Japan. Canaan's AI facial recognition module uses the Company's self-developed Kendryte K210 AI chip, designed specifically for processing machine vision tasks, such as facial and image recognition, and different areas of audio processing.
North America Holds Major Market Share
North America holds a significant share owing to numerous prominent AI in image recognition companies and providers such as Amazon Web Services, Inc., Google LLC, IBM Corp., and Microsoft Corp., in the region. The market growth is attributed to the increasing adoption of e-commerce and digital retail platforms, a combination of mobile computing and AI. Market players in the region developing facial recognition-based security systems for business-to-business (B2B) endeavors, particularly in providing AI solutions to the financial sector. For instance, in April 2024, Hewlett Packard Enterprise announced that CUBOX, a growing artificial intelligence (AI) facial and image recognition company developing generative AI models to train its existing visual recognition solutions using an HPE Cray XD supercomputer. The system also augments CUBOX's existing innovation focused on developing new image processing technologies. The company has embarked on investing in a business-to-consumer (B2C) AI service model, recognizing the pivotal role of generative AI in constructing various B2C service offerings.
The major companies serving the AI in image recognition market include Amazon Web Services, Inc., Google LLC, IBM Corp., Microsoft Corp., and Nvidia Corp., among others. The market players are increasingly focusing on business expansion and product development by applying strategies such as collaborations, mergers, and acquisitions to stay competitive.
Recent Development