Machine Vision Industry Market Analysis: Machine Vision as a Prerequisite for AI Empowering Various Industries
-
Visual information accounts for over 70% of all perceptual data, serving as the primary source of information. Humanoid robots represent the ideal final form of embodied intelligence development, multimodal large models are crucial for improving robot perception and interaction, and visual technology constitutes the most important component of robot perception.
For the robotics industry, China has consistently introduced supportive policies over the years. Particularly since September 2023, the government has successively issued the "Notice on Organizing the 2023 Future Industry Innovation Mission Challenge Program" and the "Guiding Opinions on the Innovative Development of Humanoid Robots." Among these, the "Guiding Opinions on the Innovative Development of Humanoid Robots" is the first top-level design document in China's humanoid robot field, elevating humanoid robots to a national strategic level. This indicates that the Chinese humanoid robot industry is expected to experience explosive growth within the next 2-3 years.
Machine vision is a branch of artificial intelligence technology, typically referring to a comprehensive technology that includes image processing, mechanical engineering, control, electrical lighting, optical imaging, sensors, analog and digital video technology, and computer hardware and software. Currently, the AI industry is witnessing a historic development opportunity with embodied intelligent robots, and the gradual maturation of multimodal large model technology has created substantial market demand for 3D visual perception products in the robotics field.
Although machine vision has only been developing for a few decades, with the rise of a new global wave of technological revolution and industrial transformation, the machine vision industry has experienced rapid growth. The applications of machine vision have expanded from the initial automotive manufacturing sector to widespread use in consumer electronics, pharmaceuticals, food packaging, and many other fields.
The machine vision industry chain primarily consists of upstream raw materials and components, midstream equipment manufacturing, and downstream end-user application industries. Machine Vision Industry Market Analysis
From a depth perspective, machine vision applications cover multiple segments of the industrial chain. Taking smartphone manufacturing as an example, machine vision can be applied throughout the entire production process, including structural component production, module assembly, final product assembly, and inspection of solder paste and adhesives. For instance, the production of an iPhone requires over 70 sets of machine vision systems. Broadly speaking, machine vision serves numerous downstream industries, including automotive, 3C electronics, semiconductors, food and beverage, photovoltaics, logistics, pharmaceuticals, printing, glass, metals, and wood.
In 2022, China recorded 42 machine vision investment deals, totaling 7.741 billion yuan. Companies like "Lingyun Guang" and "Orbbec" were listed on the STAR Market, while others such as "Dazhen Technology" secured tens of millions in Pre-A round funding, "Bosch Vision" received nearly 100 million yuan in angel funding, and "Mech-Mind Robotics" completed its C+ round financing. With the increasing adoption of AI technologies in industrial applications, more enterprises are entering the field, intensifying competition.
According to data from the China Machine Vision Industry Alliance, the market size of machine vision in China reached 16.888 billion yuan in 2022.
Currently, the machine vision industry is widely applied in downstream sectors such as security, consumer electronics, photovoltaics, and lithium batteries. With the recent rise of humanoid robots and AI technologies, the machine vision industry is poised for a new wave of growth opportunities. On the evening of November 24, 2023, Orbbec announced its intention to sign an investment cooperation agreement with the People's Government of Shunde District, Foshan City, for the "3D Vision Sensing Industry Intelligent Manufacturing Base Construction Project." The company plans to invest no less than 1 billion yuan in total, including no less than 500 million yuan in fixed assets. Orbbec also stated that this investment project will help the company further expand the production scale of 3D vision sensors and LiDAR, enabling it to capitalize on the development opportunities in the embodied intelligent robotics industry and establish an AI vision and robotics vision platform in the era of artificial intelligence.
From the perspective of industrial development life cycles, the international machine vision industry has already reached maturity. It is expected that in the coming years, machine vision technologies in Europe, the U.S., and Japan will continue to innovate, and the international machine vision market is likely to maintain its current scale and continue growing. The domestic machine vision industry in China is still in its growth phase. Based on recent developments, China's machine vision industry has accumulated sufficient technology, market experience, and industry know-how, entering a phase of rapid development.
Machine Vision Becomes a Prerequisite for AI to Empower Various Industries
With continuous breakthroughs in artificial intelligence technology, machine vision has emerged as a key application and technical direction for AI deep learning. Whether in humanoid robots or autonomous driving, machine vision serves as a critical implementation path, making it an essential prerequisite for AI to empower diverse industries. Machine vision technology applies the concept of "machines replacing human eyes" in industrial manufacturing. Compared to human observation, machine vision offers significant advantages in precision, speed, adaptability, objectivity, repeatability, reliability, and information integration, representing the future direction of digital, networked, and intelligent industrial manufacturing.