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市场调查报告书
商品编码
1660714
2025 年至 2033 年机器视觉市场报告(按产品、组件、应用、产业和地区)Machine Vision Market Report by Product, Component, Application, Industry, and Region 2025-2033 |
2024 年全球IMARC Group视觉市场规模达到 141 亿美元。製造业对自动化和品质控制的需求不断增加、人工智慧和深度学习演算法的不断进步以及对高效检查的需求不断增长是推动市场发展的一些主要因素。
机器视觉,也称为电脑视觉,是人工智慧 (AI) 和影像处理领域,它使机器(通常是电脑)能够解释和理解来自世界的视觉讯息。它涉及演算法和技术的开发,使机器能够分析、处理和从影像或影片中提取有意义的见解。机器视觉系统利用摄影机或其他成像设备捕捉视觉资料,然后使用各种计算方法来检测模式、识别物体、追踪运动并执行需要视觉理解的任务。因此,机器视觉技术可应用于机器人、自动驾驶汽车、品质控制和医学影像等各个行业。
由于製造业、汽车业、电子业和製药业等行业对自动化和品质控制的需求不断增加,机器视觉系统的采用不断增加,将在预测期内刺激市场的成长。这些系统提高了生产效率,减少了错误并确保了产品品质的一致性。此外,人工智慧(AI)和深度学习技术的出现使机器视觉在影像分析和模式识别任务中实现更高的准确性和多功能性,加速了产品的采用率。此外,由于智慧城市、交通和医疗保健等各种应用领域对安全和监控的需求不断增加,机器视觉在即时监控和威胁检测方面的广泛应用正在推动市场成长。此外,摄影机、感测器和处理硬体成本的下降使得机器视觉解决方案更加实惠且可供更广泛的企业使用,从而催化了市场的成长。
人工智慧和深度学习的进步
人工智慧(AI)和深度学习的不断进步极大地提升了机器视觉系统的功能。人工智慧演算法,尤其是卷积神经网路(CNN)等深度学习技术,彻底改变了影像处理和模式辨识。凭藉从海量资料集中学习的能力,机器视觉系统现在可以准确地识别和分类物体、脸部和场景。这项进展带来了脸部辨识、自动驾驶汽车、医学影像和安全监控等应用的显着改进。随着人工智慧的不断发展,机器视觉有望变得更加复杂、适应性更强,能够应对更复杂的视觉挑战,进一步推动机器视觉领域的发展和创新。
工业 4.0 和自动化的出现
工业 4.0 的出现和不同行业广泛采用自动化是推动市场成长的主要因素。机器视觉技术在整个製造工作流程中提供自动检查、精确缺陷检测和即时品质控制,在实现这些目标中发挥着至关重要的作用。透过将机器视觉与机器人系统和物联网 (IoT) 设备结合,公司可以简化营运、减少人为错误并提高整体效率。对提高生产力和降低营运成本的不懈追求持续推动工业领域对机器视觉解决方案的需求。
应用和垂直行业的扩展
机器视觉的多功能性使其在越来越多的应用和垂直行业中广泛应用。除了传统的製造业用途外,机器视觉现在也应用于农业、医疗保健、零售和娱乐等多个领域。在农业产业,它有助于作物监测、产量预测和精准农业。在医疗保健领域,机器视觉可协助医疗诊断、影像分析和机器人辅助手术。在零售领域,它促进了无收银员结帐系统、库存管理和客户分析。此外,机器视觉越来越多地应用于娱乐和游戏中,用于手势识别和扩增实境(AR)体验。该技术能够增强流程、提供有价值的见解并改善各个领域的决策,这将刺激机器视觉市场的成长。
The global machine vision market size reached USD 14.1 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 26.7 Billion by 2033, exhibiting a growth rate (CAGR) of 6.97% during 2025-2033. The increasing demand for automation and quality control in manufacturing industries, numerous advancements in artificial intelligence and deep learning algorithms, and the rising need for efficient inspection are some of the major factors propelling the market.
Machine vision, also known as computer vision, is a field of artificial intelligence (AI) and image processing that enables machines, typically computers, to interpret and understand visual information from the world. It involves the development of algorithms and techniques that allow machines to analyze, process, and extract meaningful insights from images or videos. Machine vision systems utilize cameras or other imaging devices to capture visual data and then use various computational methods to detect patterns, recognize objects, track movements, and perform tasks that require visual understanding. As a result, machine vision technology finds applications in diverse industries, such as robotics, autonomous vehicles, quality control, and medical imaging.
The rising adoption of machine vision systems due to the increasing demand for automation and quality control across industries, including manufacturing, automotive, electronics, and pharmaceuticals, will stimulate the growth of the market during the forecast period. These systems enhance production efficiency, reduce errors, and ensure consistent product quality. Moreover, the advent of artificial intelligence (AI) and deep learning technologies that empower machine vision to achieve greater accuracy and versatility in image analysis and pattern recognition tasks has accelerated the product adoption rate. Furthermore, the widespread integration of machine vision for real-time monitoring and threat detection owing to the escalating need for safety and surveillance in various applications, such as smart cities, transportation, and healthcare, is propelling the market growth. Additionally, the decreasing costs of cameras, sensors, and processing hardware that makes machine vision solutions more affordable and accessible to a broader range of businesses has catalyzed the market growth.
Advancements in artificial intelligence and deep learning
The continuous advancements in artificial intelligence (AI) and deep learning have significantly boosted the capabilities of machine vision systems. AI algorithms, especially deep learning techniques like convolutional neural networks (CNNs), have revolutionized image processing and pattern recognition. With the ability to learn from vast datasets, machine vision systems can now accurately identify and categorize objects, faces, and scenes. This progress has led to remarkable improvements in applications such as facial recognition, autonomous vehicles, medical imaging, and security surveillance. As AI continues to evolve, machine vision is expected to become more sophisticated, adaptable, and capable of tackling even more complex visual challenges, further driving growth and innovation in the machine vision landscape.
Advent of Industry 4.0 and automation
The advent of Industry 4.0 and the widespread adoption of automation across different industries represent the major factors fueling the market growth.. In the era of smart manufacturing, businesses strive to optimize their production processes, ensure consistent product quality, and minimize defects. Machine vision technology plays a crucial role in achieving these objectives by providing automated inspection, precise defect detection, and real-time quality control throughout the manufacturing workflow. By integrating machine vision with robotic systems and the Internet of Things (IoT) devices, companies can streamline operations, decrease human errors, and enhance overall efficiency. The relentless pursuit of improved productivity and reduced operational costs continues to propel the demand for machine vision solutions in the industrial sector.
Expansion of applications and industry verticals
Machine vision's versatility has led to its widespread adoption in an expanding array of applications and industry verticals. Beyond its traditional use in manufacturing, machine vision now finds applications in diverse sectors such as agriculture, healthcare, retail, and entertainment. In the agriculture industry, it aids in crop monitoring, yield prediction, and precision farming. In healthcare, machine vision assists with medical diagnostics, image analysis, and robotic-assisted surgeries. In the retail sector, it facilitates cashier-less checkout systems, inventory management, and customer analytics. Furthermore, machine vision is increasingly being employed in entertainment and gaming for gesture recognition and augmented reality (AR) experiences. The technology's ability to enhance processes, provide valuable insights, and improve decision-making across various domains will stimulate the growth of the market for machine vision.
Vision systems dominate the market
Vision systems, also known as machine vision systems, are sophisticated technologies that enable machines to perceive and interpret visual information from the surrounding environment. These systems consist of cameras or other imaging devices, image processing software, and advanced algorithms that analyze and extract meaningful data from images or videos. Vision systems can perform various tasks, including object recognition, defect detection, measurement, sorting, and tracking. By providing machines with the ability to ""see"" and understand the world, vision systems aid in revolutionizing industries across the board.
Furthermore, they enhance automation and quality control in manufacturing, optimize processes in logistics and packaging, improve medical diagnostics and healthcare, and bolster security and surveillance systems. The increasing demand for intelligent, data-driven solutions to boost productivity, accuracy, and efficiency will propel the growth of the market as vision systems become indispensable tools for businesses across diverse sectors.
Hardware holds the largest share in the market
Hardware refers to the physical components and devices used to capture, process, and transmit visual data. It typically includes cameras, lenses, image sensors, lighting systems, frame grabbers, processing units (such as GPUs or specialized vision processors), and communication interfaces. These hardware components form the foundation of machine vision systems, enabling the acquisition of visual information from the environment. The performance, accuracy, and capabilities of the hardware directly impact the overall effectiveness and efficiency of machine vision applications.
As hardware technology advances, with improvements in sensor resolution, faster processing speeds, and higher data throughput, machine vision systems become more powerful, versatile, and accessible. Upgraded hardware allows real-time processing, higher-quality imaging, and more complex algorithms, which in turn favors the expansion of machine vision into new industries and applications, making it a major driving force behind the growth of the market.
Flaw detection represents the leading application segment
Flaw detection refers to the process of identifying defects, imperfections, or abnormalities in products or materials during manufacturing or quality control processes. Machine vision systems use advanced imaging techniques and algorithms to analyze visual data and compare it against predefined standards to detect flaws accurately and efficiently. Flaw detection plays a crucial role in ensuring product quality, reducing waste, and maintaining consistent standards in various industries such as manufacturing, automotive, electronics, and pharmaceuticals. As industries increasingly prioritize quality control and automation, the demand for reliable flaw detection solutions has grown significantly. Machine vision's ability to provide fast, non-destructive, and precise flaw detection has become a driving force behind the adoption of machine vision technology. As the market recognizes the potential of machine vision in flaw detection to optimize production processes, enhance product reliability, and reduce costs, its growth and integration across industries continue to accelerate.
Electronics and semiconductor account for the majority of the share in the market
The electronics and semiconductor industry significantly contributes to the market growth due to its rigorous demand for high-quality production and precision manufacturing processes. In this industry, the miniaturization of components and the complexity of integrated circuits require meticulous inspection and defect detection at microscopic levels. Machine vision systems offer a reliable and efficient solution for inspecting semiconductor wafers, PCBs, electronic components, and assembly processes. They ensure consistent product quality, reduce defects, and improve overall manufacturing efficiency. As technological advancements continue to push the boundaries of electronics and semiconductors, the need for advanced machine vision solutions becomes even more critical. The ability of machine vision to perform high-speed, accurate inspection and analysis enables electronics and semiconductor manufacturers to stay competitive and meet the ever-increasing demands for quality and innovation. Therefore, the growth of the electronics and semiconductor industry goes hand in hand with the expansion of the machine vision market.
Asia Pacific exhibits a clear dominance in the market
The report has also provided a comprehensive analysis of all the major regional markets, which include North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa. According to the report, Asia Pacific accounted for the largest market share.
Asia Pacific is a significant driving force behind the growth of the machine vision market due to several key factors. Firstly, the region's thriving manufacturing industries, particularly in countries like China, Japan, South Korea, and India, are increasingly adopting automation and robotics to improve productivity and product quality. Machine vision plays a vital role in these processes by providing precise inspection, defect detection, and assembly verification. Secondly, the rising demand for consumer electronics, automotive, and semiconductor products in the Asia Pacific region fuels the need for stringent quality control, which further boosts the adoption of machine vision systems.
Additionally, the increasing focus on industrial automation, Industry 4.0 initiatives, and smart manufacturing practices in the region drive the integration of machine vision technologies to optimize production processes and enhance efficiency. The rapid technological advancements and the presence of major machine vision solution providers in Asia Pacific also contribute to its driving role in the expansion of the global machine vision industry.
The market is experiencing a lower-than-anticipated demand compared to pre-pandemic levels. However, this is likely to witness a paradigm shift over the next decade with the growing integration of machine vision with edge computing and IoT devices, enabling real-time analysis and decision-making at the edge of networks, leading to reduced latency and improved responsiveness in various applications. Additionally, key players are developing 3D machine vision technologies that enable precise depth perception and object reconstruction, revolutionizing applications such as robot guidance and augmented reality. Furthermore, ongoing advancements in multispectral and hyperspectral imaging have enhanced the ability to capture and analyze data beyond the visible spectrum, leading to new possibilities in fields such as precision agriculture, medical diagnostics, and materials inspection. We also expect the market to witness new entrants, consolidation of portfolio and increased collaborations among key players to drive healthy competition within the machine vision domain.