Machine vision technology enables industrial equipment to “observe” and make rapid decisions based on visual data. Common applications include defect detection, guidance, dimensional measurement and identification. As one of the foundational technologies of industrial automation, it has long been instrumental in improving product quality, accelerating
production and optimizing manufacturing and logistics processes. Today, this mature technology is integrating with artificial intelligence (AI) and spearheading the transition to Industry 4.0.
Machine vision predates the application of AI, relying on embedded systems and algorithms to process image information and identify basic features. Traditional machine vision applications were relatively simple and required no AI, provided the image data was clear and easily distinguishable. Examples include barcodes and predictable shapes with precise patterns.
With the addition of edge computing and deep learning models, the capabilities and applications of machine vision are rapidly expanding. AI enhances machine vision, extending its role beyond quality control to tasks such as aiding workers in factories, warehouses and transportation systems, allowing them to focus on more value-added tasks.
Increasing adoption across various domains where machine vision systems play a critical role in production, inspection, quality control and process optimization.
Expanding usage and enhanced analysis accuracy through AI and deep learning algorithms.
Frequent use in ensuring manufacturing accuracy and defect detection.
Applications are growing in agriculture, healthcare, transportation, defense and aerospace.
Emphasis on product innovation and differentiation, with vendors expanding ecosystems through mergers, joint ventures and partnerships.
Given the rapid development and expanding application fields, the global
machine vision market is expected to surpass $30 billion by 2035. The Asia-Pacific region is projected to dominate due to its dense manufacturing infrastructure, with over half of the market share attributed to fully structured machine vision systems used in process control and quality inspection.
Machine vision’s vertical markets include manufacturing, healthcare, logistics and warehousing, transportation, agriculture, defense and aerospace. These industries benefit from efficiency and quality improvements, particularly in manufacturing where defect detection, identification, guidance and dimensional measurement are the most common applications.
Identifying flaws or quality issues using high-resolution industrial cameras and algorithms to compare real-time production with predefined standards.
Recognizing and verifying objects, characters or patterns using Optical Character Recognition (OCR) and barcode scanning.
Assisting robotic systems in performing precise tasks such as assembly or welding, using 3D cameras and motion control.
Ensuring products meet specified tolerances through accurate measurement of size, shape and geometry using high-resolution imaging and algorithms.
The process involves four main steps:
Acquiring image data through industrial cameras and lights.
Using image processing to extract key features for subsequent recognition.
Applying algorithms to identify objects, text and other elements.
Analyzing and acting on the recognition results.
The integration of AI improves accuracy and expands the system’s capabilities.
The technical architecture of machine vision is a comprehensive system configuration comprising multiple interconnected key components. The primary components include lights, industrial cameras and software. Additionally, components such as motion control, frame grabber and AI accelerators can be incorporated based on specific application requirements. Each of these components plays a crucial role throughout the process from image capture to decision-making and output.
At the core of the architecture is the industrial PC (IPC) or embedded system which serves as the main control center of the machine vision system. It is responsible for managing and processing overall operations.
The industrial cameras and lights are critical for image acquisition. They are typically connected to the industrial PC via RJ45 or USB interfaces, with their primary function being the capture of high-quality image data.
