Market Analysis
The global Computer vision market trends is expected to surpass a valuation of USD 41.61 Bn by 2030 with CAGR of 15.21%. It stood at over USD 9,200 Mn in 2017. The market is projected to expand amid rising applications of augmented and virtual reality. The growing adoption of VR and AR coupled with development of deep and cognitive learning can bode well for the market. Prominent use of facial recognition in latest smartphones can drive the market scope during the forecast period. Security of valued assets and investments in security applications for fortifying defenses across industries can bode well for the market. Integration of the technology into mobile applications for diagnosis of diseases will drive the need for computer vision. Engineers at the University of Cambridge have developed a mobile application for monitoring of glucose levels in diabetic patients. But lack of technical experts can restrict the market growth.
Market Segmentation
By component, it is divided into hardware and software. The hardware segment accounted for a large market share owing to affordability of semiconductor packages and rise in disposable income levels of consumers. It can reach a value of USD 26.43 billion by 2023. The market is also analyzed based on computer vision applications comprising gesture recognition, face recognition, and character recognition. Gesture recognition is expected to dominate the market owing to lack of consumer electronic devices with the capability of recognizing objects and persons. Key end-users discussed in report include transportation, agriculture, entertainment, automotive, healthcare, and consumer electronics. The healthcare sector is likely to command a huge share of the global computer vision market owing to the use of AI in cranial imaging for detection of neurological disorders at a preventive stage. On the other hand, the automotive segment is predicted to display a CAGR of 33.86% during the forecast period. Developments in vehicles from conventional to self-driven vehicles can drive the demand for computer vision in automotive systems.
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Key Players
Autoliv Inc., Keyence Corporation, Sony Corporation, Intel Corporation, Microsoft Corporation, Cognex Corporation, Nvidia Corporation, Basler AG, National Instruments, and IBM Corporation are key players of the global computer vision market.
Introduction
In the rapidly evolving technological landscape, computer vision has emerged as a groundbreaking field with immense potential. It empowers machines with the ability to perceive and interpret visual information, mimicking human vision. With applications ranging from self-driving cars to medical imaging, computer vision is revolutionizing industries across the globe. This article delves into the intricacies of computer vision, exploring its working principles, key applications, and its impact on various sectors.
Understanding Computer Vision
Computer vision involves the development of algorithms and techniques to enable machines to extract meaningful information from visual data. By combining computer science, artificial intelligence, and image processing, computer vision systems can analyze and understand images or videos, opening up a vast array of possibilities. These systems leverage machine learning algorithms to recognize patterns, detect objects, and make intelligent decisions based on visual input.
Applications of Computer Vision
- Autonomous Vehicles: One of the most prominent applications of computer vision is in the development of autonomous vehicles. By leveraging real-time image and sensor data, computer vision systems enable self-driving cars to navigate, detect obstacles, and make informed decisions on the road, enhancing safety and efficiency.
- Medical Imaging: Computer vision plays a crucial role in medical diagnostics and imaging. It enables the analysis of medical images, such as X-rays and MRI scans, aiding in the detection of diseases, tumors, and abnormalities. Computer vision algorithms can accurately segment and classify medical images, assisting healthcare professionals in making accurate diagnoses.
- Surveillance and Security: Computer vision technology is widely used in surveillance systems to monitor and analyze video feeds. It can detect suspicious activities, track objects or individuals, and identify potential threats. By automating surveillance processes, computer vision enhances security and enables prompt responses to critical situations.
- Augmented Reality (AR): AR applications heavily rely on computer vision to overlay digital content onto the real world. Computer vision algorithms track the user's environment, recognize objects, and accurately position virtual elements in real-time. This technology has found applications in gaming, interior design, and retail, providing users with immersive experiences.
- Robotics and Automation: Computer vision is a fundamental component of robotics and automation systems. Robots equipped with computer vision can perceive their environment, identify objects, and perform complex tasks with precision. From industrial automation to household robots, computer vision enables machines to interact and adapt to the world around them.
Impact on Industries
The integration of computer vision across various industries is transforming business processes and unlocking new opportunities. Here are some key sectors experiencing the impact of computer vision:
- Retail: Computer vision enhances the retail experience by enabling automated checkout systems, personalized shopping recommendations, and inventory management. By analyzing customer behavior and product data, retailers can optimize store layouts, streamline operations, and provide tailored experiences.
- Manufacturing: Computer vision is revolutionizing manufacturing processes, facilitating quality control, defect detection, and production optimization. Vision systems can inspect products for defects, measure dimensions, and guide assembly robots, leading to improved efficiency and reduced errors.
- Healthcare: Computer vision is enhancing healthcare delivery by assisting in medical diagnostics, surgical planning, and remote patient monitoring. From early detection of diseases to telemedicine applications, computer vision technology is improving patient outcomes and healthcare accessibility.
- Agriculture: Computer vision is being employed in precision agriculture to monitor crop health, identify pests or diseases, and optimize resource allocation. By analyzing aerial imagery or sensor data, farmers can make data-driven decisions to maximize yields and minimize environmental impact.
Conclusion
Computer vision has emerged as a transformative technology with far-reaching applications across industries. By harnessing the power of visual data and artificial intelligence, computer vision systems are revolutionizing autonomous vehicles, healthcare, surveillance, and more.
