With the rapid development of artificial intelligence and automation technology, machine vision inspection, as an efficient and accurate means of inspection, is playing an increasingly important role in industrial manufacturing, medical diagnosis, security monitoring and other fields. Machine vision inspection simulates the human visual system and uses cameras, sensors and algorithms to identify, locate, measure and judge target objects, greatly improving production efficiency and inspection accuracy.
The first step in machine vision inspection is image acquisition. Through high-resolution cameras or sensors, the system can capture image information of target objects. The collected images are usually affected by factors such as lighting and noise, so preprocessing is required. Common preprocessing techniques include graying, filtering, edge detection, etc., the purpose is to improve image quality and facilitate subsequent analysis.
After the image preprocessing is completed, the machine vision system will extract key features in the image through algorithms. These features can be shape, color, texture, etc. Common feature extraction algorithms include SIFT (scale-invariant feature transform), HOG (histogram of oriented gradients), etc. The extracted features will be compared with the pre-trained model to achieve the recognition of the target object.
The core of machine vision detection lies in data analysis. Through algorithms such as deep learning and neural networks, the system can deeply analyze the extracted features and make corresponding decisions. For example, in industrial manufacturing, the machine vision system can determine whether the product has defects; in the medical field, the system can assist doctors in identifying the lesion area.
The ultimate goal of machine vision detection is to provide feedback for production or decision-making. Through linkage with automated equipment, the system can achieve real-time control. For example, when a product defect is detected, the system can automatically trigger the sorting mechanism to remove unqualified products.
