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The global Computer Vision market generated USD 15.19 billion revenue in 2022 and is projected to grow at a CAGR of 18.92% from 2023 to 2032. The market is expected to reach USD 85.92 billion by 2032. The market is undergoing considerable growth due to several key drivers. These include a rising demand for quality inspection and automation, an increasing need for vision-guided robotic systems, and a growing requirement for computer vision systems tailored to food applications. Furthermore, the surge in processing capabilities, improved accuracy, and the economic advantages of computer vision systems are significant factors propelling market expansion throughout the forecast period.
Computer vision is a domain of computer science and AI that centers on endowing machines with the proficiency to interpret and figure out visual details from videos and images. It seeks to replicate human visual perception by enabling computers to recognize, process, and make sense of visual data. In essence, computer vision equips machines with the capacity to perform tasks like image and video analysis, object detection, facial recognition, scene understanding, and motion tracking. Computer vision is crucial in various applications, from self-driving cars and medical image analysis to security surveillance and augmented reality. Computer vision combines various techniques, including machine learning (ML), neural networks, image processing and deep learning, to teach computers how to identify patterns, objects, and shapes within visual data. It holds the potential to automate and enhance efficiency in many industries, driving progress in the broader realm of artificial intelligence and technology.
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Advancements in Deep Learning - Deep learning techniques, mainly convolutional neural networks (CNNs), have immensely improved the accuracy and capabilities of computer vision systems. This factor has led to breakthroughs in image recognition, object detection, and image segmentation, driving the adoption of computer vision in various industries.
Increasing Availability of Data - The proliferation of digital images and videos on the internet, as well as the growth of IoT devices and surveillance systems, has provided abundant data for training and testing computer vision algorithms. More data allows for more accurate models.
Applications in Autonomous Vehicles - The development of self-driving cars and autonomous drones heavily relies on computer vision technology for real-time perception and decision-making. The automotive industry is a major driver of computer vision innovations.
Cost and Implementation Concerns - Implementing computer vision systems can be expensive, specifically for SMBs (small and medium-sized businesses). The cost of hardware, software, and skilled personnel can act as a barrier to entry.
Lack of Standardization - There needs to be standardized benchmarks and protocols in the computer vision field, making it difficult for businesses and developers to compare and choose the right solutions. This factor can lead to inefficiencies and uncertainty in adopting computer vision technologies.
Healthcare Imaging and Diagnostics - Computer vision can revolutionize medical imaging, aiding in the early detection of diseases, surgical planning, and telemedicine. The healthcare industry offers substantial growth opportunities for computer vision applications.
Retail and E-commerce - Computer vision can enhance the shopping experience through automated checkout systems, personalized product recommendations, and virtual try-ons. As online and offline retail evolves, computer vision technologies are poised for growth.
Industrial Automation - In manufacturing and logistics, computer vision has emerged as a transformative technology with applications spanning quality control, defect detection, and robotic automation. It is pivotal in enhancing operational efficiency and reducing costs for businesses in these sectors.
Data Privacy and Ethics - Using computer vision in surveillance and facial recognition technologies has raised serious concerns about data privacy, security, and ethical implications. Regulations and public opinion may restrict certain applications.
Complexity of Real-World Scenes - Computer vision systems often need help with the complexity of real-world scenes, including varying lighting conditions, occlusions, and multiple objects. Ensuring robust performance in such scenarios remains a challenge.
The regions analyzed for the market include North America, Europe, South America, Asia Pacific, the Middle East, and Africa. Asia Pacific emerged as the most prominent global Computer Vision market, with a 41.13% market revenue share in 2022.
The Asia-Pacific region, particularly countries like China, Japan, and South Korea, has been at the forefront of technological innovation. These countries have made substantial investments in research and development, resulting in the development of cutting-edge computer vision technologies and solutions. In addition, Asia-Pacific boasts a massive consumer market with diverse needs and preferences. This factor has driven the demand for computer vision applications in various industries, including e-commerce, healthcare, automotive, and manufacturing. The region is a hub for manufacturing, and computer vision technologies have been extensively adopted for quality control, process automation, and robotics in electronics, automotive, and textiles. Furthermore, Asia-Pacific has nurtured a robust ecosystem for machine learning (ML) and artificial intelligence (AI), fundamental to computer vision. It has a wealth of AI talent, research institutions, and startups dedicated to advancing computer vision. North America is expected to experience significant growth in the computer vision market over the forecast period for various reasons. The region is home to Silicon Valley, a global technology hub that attracts startups, entrepreneurs, and major technology companies. This ecosystem fosters innovation and investment in computer vision. North America hosts world-renowned universities, research institutions, and organizations with a substantial focus on artificial intelligence (AI) and computer vision research. These entities drive innovation and shape the future of the technology. Moreover, leading technology companies in North America, such as Google, Amazon, Microsoft, and NVIDIA, heavily invest in computer vision research, product development, and acquisitions. Their contributions advance the market. Besides, the region has a vibrant startup culture, with numerous startups specializing in computer vision. These startups often bring fresh ideas, agility, and innovative solutions.
Asia Pacific Region Computer Vision Market Share in 2022 - 41.13%
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The component segment includes hardware, software and service. The hardware segment dominated the market, with a share of 70.25% in 2022. Computer vision tasks, especially deep learning-based ones, require substantial computational power. Hardware components, such as GPUs (Graphics Processing Units) and TPUs (Tensor Processing Units), are essential for processing and analyzing large volumes of visual data quickly and efficiently. Additionally, many computer vision applications, including autonomous vehicles, surveillance, and robotics, require real-time or low-latency processing. Specialized hardware accelerators enhance the speed and responsiveness of these systems. Furthermore, hardware manufacturers continuously develop energy-efficient GPUs and TPUs, crucial for deploying computer vision in resource-constrained environments like edge devices and mobile platforms.
The product type segment is classified into PC-based computer vision system and smart camera-Based computer vision system. The PC-based computer vision system segment dominated the market, with a share of around 62.48% in 2022. Personal computers (PCs) offer substantial processing power, making them well-suited for computationally intensive computer vision tasks. This factor enables real-time image and video processing, which is crucial for many applications. Additionally, PC-based systems provide flexibility and customization options. Users can select the hardware components, such as CPUs, GPUs, and memory, that best suit their specific computer vision requirements. These systems are highly scalable. Users can easily upgrade or replace hardware components to accommodate increasing computational demands and the evolving requirements of computer vision applications. Besides, PCs benefit from a vast developer ecosystem. A wide range of software tools, libraries, and frameworks are available for building and deploying computer vision solutions on PC platforms.
The application segment is divided into 3D visualization & interactive 3D modelling, identification, measurement, positioning & guidance, predictive maintenance, and quality assurance & inspection. The quality assurance & inspection segment dominated the market, with a share of around 28.31% in 2022. As customer expectations for product quality rise, industries like manufacturing, automotive, and electronics require more precise quality control processes. Computer vision provides a non-invasive and highly accurate solution for inspecting and assuring the quality of products. Furthermore, many industries strive for greater automation to enhance efficiency and reduce human errors. Computer vision systems can automate inspection tasks consistently, leading to higher-quality production and cost savings. Quality assurance and inspection applications are not limited to a single industry. They are widely adopted across sectors, including manufacturing, pharmaceuticals, food, and electronics, making them versatile and in high demand.
The vertical segment is split into industrial and non-industrial. The industrial segment dominated the market, with a share of around 53.68% in 2022. The industrial sector places a strong emphasis on quality control and inspection to ensure the production of defect-free products. Computer vision technology is instrumental in automating these processes, offering rapid, precise, and consistent inspection, which is crucial for maintaining high product quality. In addition, computer vision systems improve efficiency and productivity in manufacturing and industrial processes. They can operate 24/7 without fatigue, reducing production cycle times and minimizing downtime, resulting in cost savings. By detecting and addressing defects in real time, computer vision also reduces the likelihood of defective products reaching consumers. This factor minimizes waste, lowers production costs, and enhances overall efficiency.
Report Description:
| Attribute | Description |
|---|---|
| Market Size | Revenue (USD Billion) |
| Market size value in 2022 | USD 15.19 Billion |
| Market size value in 2032 | USD 85.92 Billion |
| CAGR (2023 to 2032) | 18.92% |
| Historical data | 2019-2021 |
| Base Year | 2022 |
| Forecast | 2023-2032 |
| Region | The regions analyzed for the market are Asia Pacific, Europe, South America, North America, and Middle East & Africa. Furthermore, the regions are further analyzed at the country level. |
| Segments | Component, Product Type, Application and Vertical |
As per The Brainy Insights, the size of the computer vision market was valued at USD 15.19 billion in 2022 to USD 85.92 billion by 2032.
The global computer vision market is growing at a CAGR of 18.92% during the forecast period 2023-2032.
The Asia Pacific region became the largest market for computer vision.
Advancements in deep learning and the increasing availability of data influence the market's growth.
This study forecasts revenue at global, regional, and country levels from 2019 to 2032. The Brainy Insights has segmented the global Computer Vision market based on below-mentioned segments:
Global Computer Vision Market by Component:
Global Computer Vision Market by Product Type:
Global Computer Vision Market by Application:
Global Computer Vision Market by Vertical:
Global Computer Vision Market by Region:
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