Image Recognition Industry Overview
The global image recognition market size was valued at USD 45.02 billion in 2022 and is expected to expand at a compound annual growth rate (CAGR) of 13.4% from 2023 to 2030. Image recognition technology, powered by machine learning, has been embedded in several fields, such as self-driving vehicles, automated image organization of visual websites, and face identification on social networking websites. One of the most popular applications of image identification is social media monitoring, as visual listening and visual analytics are essential factors of digital marketing. Image recognition is highly used in applications related to safety and security, such as facial recognition used by law enforcement agencies. Furthermore, airports are increasingly using face remembrance technology at security checkpoints. For instance, in August 2019, Transportation Security Administration (TSA) conducted a short-term test for identity verification automation of the Travel Document Checker (TDC) at McCarran International Airport (LAS). This test involved facial recognition technology to assess the TDC’s ability to compare an image taken from a passenger’s identity document against the photo taken at the checkpoint.
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Major companies from various verticals, such as automotive, retail and e-commerce, security, and healthcare, are rapidly implementing digital image processing. For instance, in April 2022, Hyundai Motor Company and IonQ, the U.S.-based quantum computing company, joined forces to introduce a project to leverage quantum machine learning for image classification and 3D object detection in future mobility solutions. This collaboration entails the development of quantum techniques, utilizing IonQ’s state-of-the-art quantum computer, IonQ Aria, to enhance the recognition of various objects, including pedestrians, cyclists, and road signs. By harnessing the power of quantum computing, the project aims to achieve more efficient and cost-effective processing, ultimately contributing to the advancement of safer and smarter mobility systems.
The increasing preference among individuals for high-bandwidth data services and advanced machine learning has increased the demand for image recognition technology. Establishments among various verticals such as media & entertainment; retail; IT & telecom; and Banking, Financial Services, and Insurance (BFSI) have resulted in the increasing use of advanced technologies in their organization, which, in turn, has boosted the adoption of image recognition. The image recognition system helps to identify objects, buildings, places, logos, and people, among other images. Furthermore, recent developments in image recognition technology have allowed users to link offline content, such as brochures and magazines, with digital content, such as promotional videos, augmented reality experiences, and product information, with the help of images captured on a smartphone.
Furthermore, an automated image recognition system plays a crucial role in computer vision, which is used to identify or detect an image or an attribute in digital images or videos. It enables users to gather and analyze data in real time. The data is collected in high dimensions and produces numerical or symbolic information. As part of image recognition, computer vision enables object recognition, event detection, image reconstruction, learning, and video tracking.
Image recognition technology has witnessed several opportunities emerging in applications such as big data analytics and effective branding of products and services, owing to the extending reach of image databases. Some image databases, such as ImageNet and Pascal VOC, are freely available. The database contains millions of keyword-tagged images describing the objects in the image. It forms the basis for image recognition and enables computers to accurately and quickly identify objects in the picture. For instance, image recognition solutions quickly identify dogs in the image because it has learned what dogs look like by analyzing numerous images tagged with “dog.” Some leading social networking sites, such as Google and Facebook, have the advantage of accessing several user-labeled photos directly from their database to prepare their deep-learning networks to be highly accurate in detecting objects.
Furthermore, since the database serves as the training material for image recognition solutions, open-source frameworks such as software libraries and software tools form the building blocks of the solution. It helps to prepare or train machines to learn from the images available in the database by providing different types of computer vision functions such as medical screening, obstacle detection in vehicles, and emotion & facial recognition, among others. Some of the leading libraries for image recognition include UC Berkeley’s Caffe, Google TensorFlow, and Torch.
The COVID-19 pandemic fueled the demand for contactless solutions, leading to increased adoption of image recognition technology. Facial recognition and gesture recognition systems have gained prominence across healthcare, retail, and transportation sectors, enabling touchless access control and authentication. Moreover, image recognition technology has played a crucial role in remote work and virtual communication, facilitating virtual meetings, real-time image analysis, and enhancing visual collaboration.
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Image Recognition Market Segmentation
Grand View Research has segmented the global image recognition market based on technique, application, component, deployment mode, vertical, region:
Image Recognition Technique Outlook (Revenue, USD Million, 2017 – 2030)
• QR/ Barcode Recognition
• Object Recognition
• Facial Recognition
• Pattern Recognition
• Optical Character Recognition
Image Recognition Application Outlook (Revenue, USD Million, 2017 – 2030)
• Augmented Reality
• Scanning & Imaging
• Security & Surveillance
• Marketing & Advertising
• Image Search
Image Recognition Component Outlook (Revenue, USD Million, 2017 – 2030)
• Hardware
• Software
• Service
o Managed
o Professional
o Training, Support, and Maintenance
Image Recognition Deployment Mode Outlook (Revenue, USD Million, 2017 – 2030)
• Cloud
• On-Premises
Image Recognition Vertical Outlook (Revenue, USD Million, 2017 – 2030)
• Retail & E-commerce
• Media & Entertainment
• BFSI
• Automobile & Transportation
• IT & Telecom
• Government
• Healthcare
• Others
Image Recognition Regional Outlook (Revenue, USD Million, 2017 – 2030)
• North America
o U.S.
o Canada
• Europe
o UK
o Germany
o France
• Asia Pacific
o China
o Japan
o India
o Australia
o South Korea
• Latin America
o Brazil
o Mexico
• Middle East and Africa
o Saudi Arabia
o South Africa
o UAE
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Key Companies profiled:
• Blinkfire Analytics, Inc.
• Gumgum, Inc.
• Kairos AR, Inc.
• SparkTrendz
• Cloudsight, Inc.
• Chooch.com
• Google
• Attrasoft, Inc.
• Catchroom
• Hitachi, Ltd.
• Honeywell International Inc.
• LTUTech
• NEC Corporation
• Qualcomm Technologies, Inc.
• Slyce Acquisition Inc.
• Wikitude GmbH
Recent Developments
• In May 2023, Portuguese game studio MetaStudio unveiled a strategic collaboration with Immutable, a prominent Ethereum Layer 2 scaling solutions provider. This partnership is expected to revolutionize the gaming metaverse by introducing innovative technologies and advancements. With MetaStudio’s expertise in game development and Immutable’s cutting-edge scaling solutions, the collaboration aims to redefine the gaming experience and push the boundaries of what is possible in the virtual world.
• In April 2023, Philips and AWS collaborated to migrate Philips HealthSuite Imaging PACS to the cloud, enabling the advancement of AI-powered tools to assist clinicians. Its expanded collaboration with AWS aims to facilitate the development and implementation of generative AI applications. These applications will enhance clinical workflows, ensure efficiency, and improve diagnostic capabilities. By harnessing the power of the cloud and AI, Philips and AWS are dedicated to driving innovation in healthcare and providing clinicians with advanced tools to deliver better patient care.
• In November 2022, NEC Corporation commenced promoting its advanced multimodal biometric authentication solution, the flagship offering under its “Bio-IDiom” brand. This groundbreaking solution is the first to integrate NEC’s industry-leading face recognition and iris recognition technologies, acknowledged as the world’s top performers by the US National Institute of Standards and Technology (NIST). Starting today, NEC is introducing this solution to the Japanese market, with plans for a global release in the spring of 2023. This innovative authentication solution signifies NEC’s commitment to delivering cutting-edge biometric solutions to meet the diverse needs of customers worldwide.
• In July 2022, Clarifai, the major AI platform specializing in unstructured image, video, text, and audio data, unveiled Clarifai Community, a new complimentary service. The Clarifai Community aims to empower individuals to create, share, and utilize AI capabilities globally. Leveraging Clarifai’s comprehensive platform, known for its end-to-end AI lifecycle management, this service caters to the needs of data scientists, developers, and even non-technical business users. With Clarifai Community, users can access powerful AI tools, fostering collaboration and innovation across various domains.
• In May 2022, Hitachi, Ltd. introduced Lumada Inspection Insights, an all-inclusive digital solution suite for inspecting, monitoring, and optimizing vital assets. Developed by Hitachi Energy and Hitachi Vantara, Lumada Inspection Insights allows customers to automate asset inspection processes while driving sustainability initiatives, enhancing physical security, and mitigating risks associated with storms or fires. The solution, integrated with advanced artificial intelligence (AI) capabilities, employs powerful analysis of photographs and videos, including LiDAR, thermal, and satellite imagery. This comprehensive offering empowers organizations to streamline asset management and make informed decisions to ensure operational efficiency and resilience.
• In November 2021, the Snapdragon Spaces XR Developer Platform was introduced to facilitate the creation of augmented reality (AR) experiences that seamlessly adapt to the surrounding spaces. With a primary focus on developers, the platform integrates established technology and an open ecosystem, enabling exploring new possibilities in spatial computing. This innovative platform paves the way for the advancement of AR applications, offering immersive experiences that seamlessly blend digital content with real-world environments.