A brief discussion on machine vision detection technology and machine vision positioning technology

Machine vision inspection and machine vision positioning are two important machine vision application technologies, the main difference lies in the different inspection objects and application fields. Machine vision inspection technology can be used to inspect the appearance, size, sealing, moving objects, color defects, shape defects, etc. of products, and is widely used in industry, medical care, electronics, agriculture and other fields; while machine vision positioning technology can realize the positioning of products and obtain position information, and is widely used in industrial production lines, medical equipment, electronic products, agricultural machinery and other fields. This article explores and summarizes the differences and applications of these two technologies.

Machine vision detection refers to the process of identifying and locating targets with specific features in images or videos, usually involving tasks such as target recognition, target tracking, and target segmentation. It is one of the most core and basic technologies in the field of machine vision and has broad application prospects.

Machine vision inspection technology mainly includes the following aspects:

1. Feature extraction: Various feature extraction algorithms can be used to extract key features of the target, such as color, shape, texture, etc., from images or videos.

2. Feature matching: Compare the extracted target features with known target features to find the location of a specific target in the image or video.

The application of machine vision inspection is very extensive, including but not limited to the following aspects:

1. Defect detection: such as checking whether products have defects in manufacturing.

2. Security monitoring: such as target identification and tracking in video surveillance systems, automatic alarm systems, etc.

3. Autonomous driving: such as pedestrian recognition and vehicle detection in driverless cars.

4. Medical diagnosis: such as automatic diagnosis of medical images such as X-rays and MRIs, detection of human organs and cells, etc.

Machine vision positioning refers to the process of determining the position and posture of a camera relative to a scene by extracting and matching features of a known object or scene. It is one of the important technologies in the field of machine vision, involving issues such as camera parameter calibration, feature extraction and matching, and pose estimation. Machine vision positioning mainly solves the problems of reconstruction and precise positioning of objects in three-dimensional space.

Machine vision positioning technology mainly includes the following aspects:

1. Camera calibration: Determine the internal and external parameters of the camera and determine the mapping relationship between the image coordinate system and the actual coordinate system.

2. Feature extraction and matching: Extract object features in the environment and perform matching searches in the image to find the location of specific objects.

3. Pose estimation: Use the camera parameters and feature matching results to estimate the translation and rotation parameters of the object relative to the camera.

The application of machine vision positioning technology mainly includes the following aspects:

1. Unmanned driving: Automatic driving of vehicles is achieved by locating roads and road signs.

2. Industrial automation: Position and identify different objects to achieve intelligent production.

3. Robot navigation: Use machine vision positioning technology to enable the robot to navigate autonomously in complex environments.

4. Aerial mapping: Use machine vision positioning technology through aerial photography to quickly map the terrain of a large area.

Machine vision positioning technology has a wide range of applications in various fields, providing effective support for achieving goals such as automation, intelligence and precision.

Although machine vision inspection and machine vision positioning are both important technologies in the field of machine vision, their application scenarios and task objectives are different.

Machine vision inspection refers to the process of finding specific objects in images or videos, which often involves tasks such as target recognition, target tracking, and target segmentation. Its core task is to identify and distinguish different targets, and it can be applied to defect detection on industrial production lines, automotive driving assistance, security monitoring, and other aspects.

Machine vision positioning refers to determining the position and posture of the camera relative to the scene by extracting and matching features of known objects or scenes in a specific scene. Its core task is to measure or restore the three-dimensional spatial position and posture of the target or scene. Machine vision positioning has a wide range of application scenarios, such as robot navigation, unmanned vehicles, aerial surveying and mapping, virtual reality, etc.

The difference between the two lies in their targets. Detection is to search for the target in the scene when the target’s location is uncertain; positioning is to measure the target’s position and posture in the scene when the target’s location is already known.