Computer Vision Systems Market Size - By Deployment Mode, By Component, By Application, By Industry Vertical, Growth Forecast, 2025 - 2034

Computer Vision Systems Market Size

According to a recent study by Global Market Insights Inc., the global computer vision systems market size was estimated at USD 20.9 billion in 2024. The market is expected to grow from USD 24.7 billion in 2025 to USD 111.3 billion in 2034, at a CAGR of 18.2%.

• Computer vision systems market is growing, which is fueled by developments regarding artificial intelligence (AI), machine learning, and sensors. The main drivers are the growing automation demand in a variety of industries such as manufacturing, automotive and retailing industries where vision systems increase efficiency, quality control and safety.
   
• The healthcare sector puts these systems to use in terms of diagnostics and monitoring of patients, whereas real-time threat detection also improves security and surveillance. Vision technologies are finding applications in agriculture in the form of precision farming and in smart cities in urban management. Vision is integrated in consumer electronics to make the devices interactive and in the energy sector to monitor infrastructure.
   
• In March 2024, MIT CSAIL researchers invented an algorithm called FeatUp, showed major improvements in the resolution of deep networks applied to a computer vision system. This development enables algorithms to detect not only high and low-level information but also enhances the work on such tasks as object detection and scene parsing.
   
• FeatUp increases image resolution creating high-resolution features using low-resolution input features, which solves the former shortcoming of pixel clarity. Due to its potential to give detailed information, the algorithm can be applied to solutions such as autonomous driving and medical imaging, where more efficient and trustworthy results can be achieved in a range of computer vision tasks.
   
• The computer vision systems market growth is driven by the emergence of Industry 4.0, smart infrastructures, and autonomous cars. Edge computing and cloud-based vision solutions are emerging; these can be scaled in real-time processing. Integration with IoT increases data-driven decision-making, and developments in deep learning can increase the accuracy of the system.
   
• New opportunities are being opened by emerging applications in the AR/VR and robotics field. The investment trend of sustainability and operational efficiency in various industries is still maintaining, and businesses working on pioneering cost-effective and multi-purpose vision solutions to accommodate the needs of diverse industries underlines a competitive medium where the market is rich and fast-changing.
   
• The computer vision systems market is propelling, as AI technologies are becoming more advanced and there is growing interest in automation in every industry. Firms use the systems to improve operational efficiency, make better decisions and offer novel solutions. In production the use of computer vision drives quality control and robotic automation, making manufacture efficient.
   
• These systems are being adopted in healthcare to accomplish advanced diagnostics and patient monitoring which can lead to personalized care. Customer behavior analysis in retail stores and inventory management is leveraged using technologies in sight to boost customer experiences along with their shopping activities. Computer vision is implemented in the automotive industry, changing mobility in self-governing navigation systems and security. Application in security and surveillance is also growing, where threat detection and analytics are now performed in real-time and enhance safety.
   

Computer Vision Systems Market Trends

• The cloud-based computer vision systems industry is growing steadily, with the growing demand related to scalability and flexibility. Traditional capabilities like data-processing and analysis of large visual information are used by businesses through the use of cloud infrastructure to store and analyze important data without the huge expense of on-site hardware. These models accommodate real-time applications such as facial identification, monitoring, autonomous vehicle system and they take advantage of the seamless updates and integrations with AI platforms.
   
• The moves by enterprises are cloud-based, where the providers provide a pay-as-you-go basis, which is affordable to small and medium-sized enterprises due to its provision of high-technology in terms of vision. The capacity to consolidate data storage and processing systems facilitate harmonization and promotes international activities.
   
• Correlating with the other cloud-based services, including machine learning and analytics, further promotes the utilization in industries, including retail, healthcare, and the manufacturing business. The shift toward cloud-based solutions keeps gaining momentum as organizations focus on the concepts of agility, scalability, and accessibility of top-level computer vision capabilities with the location being of no importance anymore.
   
• Computer vision on premises solutions is still the favored option among institutions that value control and security as well as customization. Such a deployment model allows businesses to keep sensitive visual data in their infrastructure and thus meet the requirements of strict regulation in the areas such as healthcare, finance, and government. Applications of these systems used by companies include industrial automation, quality control and surveillance, where resources may be in the form of specialized hardware, offering the ability to perform specialized processing tasks with high performance.
   
• On-premises options allow localized customizations to support the particular requirements that they are known to deliver low-latency capability essential to time-sensitive applications such as robotics and manufacturing. This trend is reinforced by the hardware improvements, e.g., high-power GPUs, which improve the local processing capacity of complicated vision algorithms. Companies that have legacy systems, or those which centralize their data to a large degree by virtue of having strong data sovereignty concerns, still invest in on-premise deployments since they desire to have total control over their computer vision infrastructure and processes.
   

Computer Vision Systems Market Analysis

Based on deployment mode, the computer vision systems market is divided into cloud-based, on-premises, and edge-based. The cloud-based segment dominated the computer vision systems market accounting for around 37% in 2024 and is expected to grow at a CAGR of over 19% from 2025 to 2034.
 

• The scalability, flexibility and cost-effectiveness of computer on cloud have made it popular. The model enables organizations to harness remote computing power to process and analyze visual data with comparatively less on-site infrastructure. With the capability of applying cloud computing, it supports diverse applications that span across real-time image processing to advanced analytics. That possibility means that businesses are capable of working with tremendous volumes of data, combining machine-learning models, and quickly applying computer vision systems.
   
• Systems that feature cloud-based allow easy updates and maintenance to keep organizations up-to-date with the most recent developments in computer vision technology. This deployment model is of special interest to industries with dynamic scaling needs, which include retail, healthcare and smart city projects where data processing needs change dynamically.
   
• The cloud also facilitates remote access, and teams can collaborate even at geographical distances all the while taking advantage of centralized vision processing tools. This encourages innovation through fast prototyping and a flexible deployment of computer vision applications that do not require high investment in hardware up front. Moreover, cloud-based services help combine with other new technologies such as artificial intelligence and big data analytics, which will further increase the potential of computer vision systems.
   
• Computer vision on-premises systems are still a key aspect in organizations that consider high-priority control, security, and low-latency computations. The model includes running vision systems on local hardware where data is within the organizational infrastructure. It is better suited to those applications that need real-time processing, like industrial automation or secure surveillance, in which latency cannot be sacrificed.
   
• Computer vision systems are changing the industry in the form of edge-deployed systems, which analyze visual data near the source. The model is latency-reducing, increases real-time decision-making, and optimizes bandwidth utilization, thus finding optimal application in solutions such as driverless cars or intelligent surveillance. Edge deployment is applicable in distributed environments and allows vision systems to be used in remote or connectivity-deficient settings.
   

Based on component, the computer vision systems market is segmented into hardware, software, and services. The hardware segment dominates the market with 66% share in 2024, and the segment is expected to grow at a CAGR of over 18% from 2025 to 2034.
 

• The hardware segment plays a central role in computer vision systems market in terms of an anchoring juncture to visual data capture, process and analysis. It includes a variety of elements, such as cameras, processors, memory, storage and display units, and each is designed to accommodate the needs of varied applications in various types of industries including manufacturing, healthcare, and automotive. The combination of AI with specialized hardware allows improving the functioning of a system and being able to complete such complex tasks as object detection and face recognition.
   
• Advances in hardware are also contributing to the reduction in energy consumption and scalability which is making computer vision solutions more viable to even large enterprises and smaller entities. Edge computing has also supported the significance of small devices with great performance in real-time analytics that have to be analyzed in places where latency is a crucial issue.
   
• The computer vision systems market is propelled by the software segment which consists of platforms, frameworks, and applications in order to analyze and process visual information. The types of software that assist in challenging issues such as object detection, image classification and video analytics are getting more sophisticated and use AI and deep learning to increase accuracy. The democratization of access is being enabled by availability of open-source tools and pre-trained models and developers are able to develop customized solutions in industries such as healthcare, automotive, and retail.
   
• The services segment facilitates maintenance and installation of computer vision systems including professional and managed services. Such services can guarantee smooth integration, most effective use, and support to vision solutions throughout industries. The need in services is increasing as business needs experience to implement sophisticated systems and to get the best of them. Other ways in which services are developing include the cloud-based management and AI-based consulting that is more scalable and accessible.
   

Based on application, the computer vision systems market is segmented into facial recognition, image classification, object detection, object tracking, object detection, object tracking, optical character recognition, image segmentation, automated optical inspection, 3d vision and depth sensing, gesture recognition, and others. Object detection identifies and locates objects within images or videos, enabling precise analysis for various applications. Using deep learning, it pinpoints objects’ shapes, sizes, and positions, supporting tasks like inventory management and autonomous navigation.
 

• The retail inventory management can support object detection and automatically tracks the stock and monitors the shelves. It can determine product availability, placement and level of stocks by analyzing camera feeds, minimizing cases of out of stocks. It works with integrated AI and offers real-time information, which allows retailers to maximize stock and customer experience. It is scalable and suits large retailing chains so that there is less waste and more efficiency.
   
• In manufacturing defect detection, object detection identifies defects in product or component during manufacturing. Through image analysis of production lines, it accomplishes quality insurance which alleviates wastage and guarantees conformity. It can be combined with the AI to perform real-time detection allowing the automation of such industries as electronics and automotive.
   
• Facial recognition technology is a staple of computer vision that uses sophisticated algorithms to positively determine the identity of people using facial characteristics. Its implementation has grown exponentially to all industries because of its potential to deliver secure, effective and personalized solutions. It applies deep learning models, more concretely convolutional neural networks, to examine facial patterns with great accuracy, which allows real time processing. Facial recognition is changing how people approach security, access control, and customer experiences as it provides convenient identity verification and behavioural analysis.
   
• Security and surveillance Facial recognition Face recognition is transforming predominantly the realm of security and surveillance in terms of both ensuring people and architectural security and detecting threats. It can also be used in identifying subjects in real time by analyzing real-time input or previously recorded video and thus allowing the immediate response to potential threats. Coupled with smart cameras and AI, they improve the surveillance of crowded places, airports, and other important infrastructure. Using sophisticated algorithms that will make it near accurate, in crowded or low-light settings it will be a highly effective continuous-monitoring tool.
   
• Object tracking tracks objects in video frames, and thus, it gives the capability of constant tracking in different applications. It preserves object invariance even under dynamic conditions, and it is used to support on-the-fly analytics, using AI algorithms. It works in combination with IoT and cloud computing, which increases its scalability, so it is suited to surveillance, retail, and manufacturing. Tracking objects enhances operational efficiency and decision-making through actionable information gained out of the visual data.
   

Based on industry vertical, the computer vision systems market is segmented into manufacturing, healthcare, retail, automotive, security and surveillance, agriculture, smart cities, consumer electronics, energy and utilities, others. Computer vision systems are revolutionizing manufacturing by enhancing automation and precision across production processes. These systems leverage advanced imaging and AI-driven analytics to streamline operations, ensuring high-quality output and operational efficiency.
 

• Computer vision plays a central role in the electronics and semiconductor sector and makes precision manufacturing possible in high stakes production. AI-powered systems have high-resolution imaging and meticulous quality control by detecting the presence of even the smallest defects in delicate parts. The technology also facilitates automatic checks, which bring about efficiency in the high production industries.
   
• Visual systems relate with robotics to bring on-point positioning of components and monitoring processes which are in line with the need of miniaturization and quality standards. Complex manufacturing processes further require defect detection and assembly precision refinements with the adoption of 3D vision and deep learning. 
   
• When used in display manufacturing, computer vision solutions guarantee better quality production of displays used in various devices such as Smartphones and TVs. Advanced imaging is applied to such systems where any kind of defects like scratches, malfunctioning pixels, or color variation are detected to provide the perfect output. Analytics will provide the possibility to monitor the process in real-time, adapting to different production situations with AI. Vision systems facilitating accurate assembly and alignment is imperative in high resolution displays. 
   
• Computer vision is applied to the PCB assembly connection through its ability to control the accurate placement of components and examination of solder junctions. The misalignment, soldering errors, or component omissions are identified by their high-resolution cameras and AI algorithms that guarantees reliable circuit boards. Automatic assembly lines are enhanced by vision systems resulting in an increase in the speed and accuracy of the assembly line. The shift to real-time analytics enables corrections in real time and minimizes mistakes.
   
• The revolution in healthcare is computer vision, which has boosted diagnostics, monitoring, and efficiency of operations. AI-based solutions help in analyzing medical images, patient monitoring, and surgery where it has increased higher accuracy and outcomes. Technology facilitates real time analytics that makes decisions to be made faster. There is ability to connect to IoT and robotics which improves the delivery of healthcare that is in line with the digital health trend. There is less human error and vision systems enable precision in critical applications.
   

US dominated the computer vision systems market in North America with around 90% share in 2024 and generated USD 5.9 billion in revenue.
 

• US Computer vision systems industry is prospering since it has a well-developed technological foundation and is widely used among other sectors. The area is in the forefront of applying artificial intelligence (AI) with computer vision making applications in the medical, automotive sectors and security.
   
• There is increasing demand of computer vision in operation within autonomous cars and smart manufacturing with strong push towards digital transformation. The developed IT and telecommunication infrastructure of the region allows the implementation of cloud and edge-based vision systems and scalable and resource-optimal systems. The growing interest in Computer vision in the retail sector in managing inventory, and offer personified customer experiences is another emerging trend and a contributing factor to the desire to automate certain parts of the operations in the region.
   
• The NA’s computer vision market is dominated by the U.S., as it is a global leader in AI development research and tech giants are concentrated there. Its major strengths in the country are in the development of state-of-the-art vision systems in autonomous cars, healthcare diagnosis, and security systems. Thanks to industry 4.0, rapid evolution is the application of computer vision to monitoring quality during manufacture and to predictive maintenance work.
   
• Customer experience in retail and e-commerce sectors harness the use of vision technologies including automated checkout facilities. The U.S. has had considerable investment in both cloud computing and edge devices, and real-time data processing of vision applications are a major strength in the U.S.
   
• The computer vision systems market in Canada is growing as it is committed to AI-oriented innovation and smart city development. The nation is launching vision systems in medical care to do complex diagnostics and in agriculture to execute precision farming.
   
• Industries in Canada, specially manufacturing and logistic industries are embracing computer vision as a means to automate, and boost process efficiency through quality control inspection and material handling. The ecosystem is supported by the government to research and develop AI and the image recognition and 3D visualization advancement is amplified by the numerous universities and tech hubs that use the technology.
   
• The computer vision systems market is driven in Germany by its advantageous position in automotive and manufacturing industries. This nation uses the vision system to integrate in the development of autonomous vehicles, and smart factories, which improve quality control and robotics. Predictive maintenance and vision-assisted process automation using AI are promoted through industry 4.0 endeavors.
   
• The computer vision systems market of Germany is steadily growing due to its ambitions towards Industry 4.0 and automation. The area is leading in the use of vision systems in production, automotive industry, and logistical applications to improve such activities as quality control and robotics navigation. Germany is also spending in artificial intelligence and machine learning to enhance computer vision, especially in autonomous driving and intelligent surveillance.
   
• The market in the UK is developing on the basis of its emphasis on AI innovation and smart city initiatives. Traffic management and automated checkout and inventory monitoring are also being introduced in the country where vision systems are being integrated in transportation as well as in retail. The usage of healthcare applications is expanding, and vision technologies contribute to the process of diagnostics, as well as patient monitoring.
   
• The advantage of the UK as an AI research ecosystem, which boasts a number of tech centres backed by universities, facilitates the development of image recognition and facial analytics. Ethical AI Government efforts encourage the use of vision systems in surveillance and security to be adopted responsibly. Using cloud and edge computing optimizes data processing in real-time to accommodate a variety of applications. The UK also has the developed vision-based authentication systems due to its leadership in fintech.
   
• The advanced image sensor and 3D vision systems deployment is backed by Germany precision engineering approach. Vision technologies are also being used in the retail and logistics industries to manage inventory and to receive automatically via automated warehousing. With government support of AI research and the robust industrial base, the country is a market leader in Europe when it comes to computer vision.
   
• The computer vision systems market in China is projected to witness strong and sustained growth throughout the forecast period from 2025 to 2034.
   

The computer vision systems market in China is projected to witness strong and sustained growth throughout the forecast period from 2025 to 2034.
 

• China leads the Asia Pacific computer vision market through aggressive adoption of AI and government support. The nation is the world leader in facial recognition and surveillance, including vision systems into cities of the future and security. Vision is used through automated manufacturing processes, automation of manufacturing processes, and in quality control. Visual marketing is also used in e-commerce in inventory tracking and customer analytics.
   
• The Chinese healthcare sector considers the vision of progressive diagnostics, which is supported by its New Generation AI Development Plan. The huge datasets and edge investments in the country further boost real-time vision applications, and China is currently leading in the development of innovations in computer vision.
   
• The computer vision industry in India is expanding at a fast rate due to the digital economy and various applications. Vision is deployed in the agriculture sector where precision farming is employed, and in the healthcare sector where scans are made and remote access to care is provided. Retail and online stores are using vision to manage inventory and provide individual experience to customers.
   
• The vision systems used in the automation and quality control manufacturing industry in India fit into the landscape of quality manufacturing in India through Make in India. The booming of cloud computing and edge devices leads to the possibility of scalable vision solutions, facilitating the tech-driven development of India.
   
• The computer vision systems market is emerging in Japan because of its high positions in the setting of robotics and automobiles. Smart factories use vision systems to facilitate quality assurance and automation. Vision-based elder care robotics, as well as healthcare diagnostics are in demand due to the aging population of the country. Retail industries implement a customer analysis and stocks vision. Japan is more concerned with the development of AI and the fact that the government takes steps toward the digitalization of companies, which contributes to market expansion. The collaboration of edge computing and 5G enables real-time vision systems, which makes Japan an innovator in the area.
   

The computer vision systems market in Brazil is projected to witness a notable increase in market share from 2025 to 2034, driven by rising adoption across key industries.
 

• The computer vision market in Brazil is developing due to the rising rates of digitalization and business automation. The vision systems that the region implements in manufacturing are as such that relates to quality control and in agriculture on precision farming. The retail industries are applying the vision to inventory control and customer intelligence and the smart city projects on traffic control and surveillance. The investments in AI and digital infrastructure made by governments contribute to the markets growing. The emergence of the cloud computing which has resulted in the concept of scalable vision solutions is also spurring its application in various sectors in the region.
   
• The computer vision business is growing in Brazil because this country pays attention to agriculture and manufacturing. Smart factory involves precision farming and quality control by the use of vision systems. The retail applies a vision to customer analytics and inventory tracking. The smart city projects in Brazil use vision to watch and handle traffic.
   
• The computer vision market in Mexico is developing at a rapid pace with the help of its manufacturing and automobile industries. Smart factories have vision systems that are employed in quality assurance and automation. Retail will use vision to manage inventory and analyze the customer, and agriculture will use it to perform precision farming. Implementation of the cloud computing strategy increases scalability of the vision systems to aid the growth of the Mexican industries and economy.
   
• The computer vision systems market in Saudi Arabia is anticipated to capture a growing share of the regional market between 2025 and 2034, supported by increasing investments in automation and smart technologies.
   
• The Saudi Arabia computer vision market is an emerging market and this is due to digitalization and smart city investments. The region embraces vision systems in productions as automation and in security as a surveillance system. Vision is used to perform diagnostics in healthcare sectors, and it is used by retail to perform customer analytics. State investments in AI and digital infrastructure promote the growth of the market. The emergence of cloud and edge computing promotes scalable real-time vision application increasing the efficiency of operations among industries.
   
• The computer vision market in South Africa is growing due to its interest in security and industrial automation. The vision systems are used to monitor and control the quality during manufacturing. In retail, vision is used in customer analytics and inventory management, whereas in the agricultural sector, precision farming.
   
• Computer vision Saudi Arabia market is on the rise due to the vision 2030 initiative and smart city development activities. Urban planning integrates vision systems into the field of surveillance and traffic management. Vision is used in manufacturing industries in terms of automation and quality assurance as well as healthcare by diagnosis.
   

Computer Vision Systems Market Share

• The top 7 companies in the computer vision systems industry are NVIDIA, Microsoft, Intel, Teledyne, IBM, Google, Amazon Web Services, contributing around 30% of the market in 2024.
   
• NVIDIA is the force behind the boom in computer vision by investing heavily in AI-powered GPUs and platforms such as Jetson (edge computing). The company bets on the growth of the AI Enterprise suite, which is set to combine generative AI to power more powerful autonomous vehicle and robotics vision solutions. Collaborating with automotive and healthcare companies provides strategic reinforcements to its ecosystem, and with its open-source contribution such as CUDA, it attracts developers. NVIDIA focuses on real-time analytics and rolling out using 5G. New measures involve developing new synthetic datasets that would better train the models along with the expansion to working with smart cities in serving their traffic and surveillance needs.
   
• Microsoft continues to drive increases in computer vision with Azure AI Vision, which includes cloud-based applications to process images in real-time. The company collaborates with the hardware giants such as NVIDIA to optimize performance in various sectors such as retail and healthcare. Developing generative AI, Microsoft focuses on enterprise use cases through enhancing object detection and facial recognition. New approaches will involve growing edge computing abilities to enable on-device vision processing and exploiting open-source frameworks to appeal to developers.
   
• Intel drives its market share in computer vision through AI- optimized chips (Gaudi) and edge computing in OpenVINO. Its markets include automotive and industrial with the focus on vision-guided robotics, and ADAS. A key example is strategic acquisitions, i.e., Mobileye, to boost capability in autonomous driving. New approaches such as 5G integration into real-time analytics and growth of cloud-to-edge implementations towards smart manufacturing are arising. Intel works with software developers to optimize the vision algorithms by developing an open-source ecosystem. Research into 3D vision and IoT connections is aimed to help serve smart cities and health care diagnostics, opening up innovation and market penetration opportunities.
   

Computer Vision Systems Market Companies

Major players operating in the computer vision systems industry are:

• NVIDIA
• Microsoft
• Intel
• Teledyne
• IBM
• Google
• Amazon Web Services
• Cognex
• Basler
• Qualcomm
   
• Competitive environment in the computer vision systems market is dynamic and evolves fast due to technological advancement, partnerships strategy and increased extension of the industry. The main vendors, including Intel, NVIDIA, IBM, and Microsoft, are influencing the market in the scenario of unrelenting R&D and the incorporation of AI-enabled features, into their vision’s platforms. These corporations dwell on the improvement of real-time image and video analysis, object identification, face recognition, and tracking in order to serve such industries as automotive, healthcare, and scoring in manufacturing and retail.
   
• Smaller companies and mid-sized companies too are taking shape with their own specialty solutions in niche areas like gesture recognition, surveillance analytics and medical imaging. Its nimble dexterity and the orientation towards innovation allow them to release innovative tools that are able to compete favorably with incumbents. Such democratizing technologies as open-source computer vision packages such as OpenCV enable smaller players, which can produce competitive products.
   
• Hardware manufacturers usually partner with software providers and system integrators. Through these partnerships, there is the capability to achieve end-to-end solutions by integrating both edge computing, cloud resources and machine learning algorithms. The combination of computer vision and such technologies as augmented reality, robotics, and IoT is further expanding the market scope and intensifying competition.
   
• With the maturation of the market, another factor that ensures differentiation is the precision of the vision algorithms, the speed of processing, compatibility with multiple environments and ease with which it can be integrated with the current IT ecosystem. The firms are investing in flexible and expandable systems to address various industrial requirements and make a competitive environment highly dynamic and innovative.
   

Computer Vision Systems Industry News

• In April 2025, Keyence released a new line of vision sensors, the IV4 series, which includes built-in AI functions AI Identify, AI OCR, AI Count and AI Trigger. Such sensors have versatile installation capabilities of 50 mm to 3 meters range with up to 15,000 parts per minute detection capabilities without the requirement of a dedicated PC since it can do all of that internally within the sensor.
   
• In March 2025, Himax technologies declared that it will demonstrate its visionary wiseEye AIoT products as well as its next generation Liqxtal LC optical application at the embedded world 2025 in Nuremberg, Germany. Most of the WiseEye technology includes ultralow-power AI-sensing produced in the WiseEye2 processor, which has the PSA accreditation, and advanced modules of biometric credentials, as well as thermal sensing.
   
• In September 2024, Basler released pylon AI that is a new image analysis software with sophisticated functionality aimed at challenging machine vision application tasks within the industry. Users can do object detection, classification, and segmentation using deep learning models without any programming resources because of this tool. As a part of the pylon Software Suite, pylon AI has a drag-and-drop interface, allows benchmarking performance on diverse hardware platforms, and supports several common AI frameworks: PyTorch, TensorFlow, and NVIDIA TAO.
   
• In April 2024, Cognex released In-Sight L38, the first AI-powered 3D vision system designed to automate assembly and manufacturing lines and build automation. The system integrates AI, 2D and 3D vision technology to conduct checks and measurements that are trusted and ease the configuration process with embedded AI technology and pre-trained models. The In-Sight L38 has the patented, speckle-free laser optics and high powered laser providing high rate acquisition and supports high line speeds on Class 2 safety products.
   

The computer vision systems market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue ($ Mn/Bn) from 2021 to 2034, for the following segments:

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Market, By Deployment Mode

• Cloud-based
  • Public cloud
  • Private cloud
  • Hybrid cloud
• On-premises
  • Enterprise deployment
  • Industrial deployment
• Edge-based
  • Edge computing devices
  • IoT-integrated systems
  • Smart cameras and sensors

Market, By Component

• Hardware
  • Cameras And Image Sensors
    • Industrial Cameras
    • Smart Cameras
    • 3D Cameras
    • Infrared Cameras
  • Processors And Computing Units
    • CPUs
    • GPUs
    • FPGAs
    • ASICs
    • Edge AI Processors
  • Memory And Storage
  • Display Units
  • Others
• Software
  • Computer Vision Platforms
  • Deep Learning Frameworks
  • Image Processing Software
  • Analytics Software
  • Custom Applications
• Services
  • Professional Services
    • Consulting Services
    • Integration And Implementation
    • Training And Support
  • Managed services
    • Cloud-based services
    • On-premise services

Market, By Application

• Facial recognition
  • Security and surveillance
  • Access control
  • Emotion recognition
  • Marketing and customer analytics
• Image classification
  • Product categorization
  • Content moderation
  • Medical image analysis
  • Industrial classification
• Object detection
  • Retail Inventory management
  • Manufacturing defect detection
  • Security applications
  • Autonomous systems
• Object tracking
  • Surveillance and security
  • Sports analytics
  • Retail customer tracking
  • Manufacturing process monitoring
• Optical Character Recognition (OCR)
  • Document digitization
  • License plate recognition
  • Text recognition in manufacturing
  • Retail applications
• Image Segmentation
  • Medical image segmentation
  • Industrial applications
  • Retail applications
  • Autonomous vehicles
• Automated optical inspection
  • Display panel inspection
  • PCB inspection
  • Semiconductor inspection
  • Consumer electronics quality control
• 3D vision and depth sensing
  • Augmented reality applications
  • Robotics and automation
  • Smart manufacturing
  • Automotive applications
• Gesture recognition
  • Consumer electronics
  • Automotive HMI
  • Healthcare applications
  • Smart home controls
• Others

Market, By Industry Vertical

• Manufacturing
  • Electronics and semiconductor
    • Display manufacturing
    • PCB assembly
    • Semiconductor production
    • Consumer electronics
  • Automotive
  • Aerospace and defense
  • Pharmaceuticals
  • Food and beverage
  • Others
• Healthcare
  • Medical imaging and diagnostics
  • Patient monitoring
  • Surgical assistance
  • Healthcare administration
  • Others
• Retail
  • Inventory management
  • Customer analytics
  • Self-checkout systems
  • Digital signage and smart displays
  • Others
• Automotive
  • Advanced Driver Assistance Systems (ADAS)
  • Autonomous vehicles
  • In-cabin monitoring
  • Smart cockpit displays
  • Others
• Security and surveillance
  • Public safety
  • Retail security
  • Industrial security
  • Residential security
  • Others
• Agriculture
  • Crop monitoring
  • Livestock management
  • Precision farming
  • Others
• Smart cities
  • Traffic management
  • Public safety
  • Infrastructure monitoring
  • Energy management
  • Others
• Consumer electronics
  • Smartphones and tablets
  • Smart TVs and displays
  • AR/VR devices
  • Smart home devices
  • Others
• Energy and utilities
  • Power grid monitoring
  • Renewable energy systems
  • Infrastructure inspection
  • Others
• Others

The above information is provided for the following regions and countries:

• North America
  • US
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Russia
  • Nordics
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • ANZ
  • Southeast Asia
• Latin America
  • Brazil
  • Mexico
  • Argentina
• MEA
  • South Africa
  • Saudi Arabia
  • UAE