This section provides overview, applications, and principles of image processors. Also, please take a look at the list of 9 image processor manufacturers and their company rankings.
An image processor is a device that processes images taken by a camera or other device to measure and analyze the characteristics of an object based on the images.
Such image processing is performed on a computer, and the results of the analysis can be reflected in other equipment.
Image processing devices make it possible to recognize the shape of objects, measure distances, and count the number of pieces. By feeding this information back to other devices that combine this information, automation of all kinds of objects becomes possible.
Image processing equipment is used in a wide range of applications, from everyday life to industrial and medical fields.
In recent years, IoT technology combined with human intelligence and machine learning has also been actively developed to automate and improve the efficiency of various human activities.
Although there are various types of image processing devices depending on the application, they are basically composed of a camera and a computer.
After images captured by the camera are transferred to the computer, they are pre-processed for image processing. What exactly is done depends on the application.
For example, when measuring the number of subjects, filter processing is used to remove noise, sharpen the image, and make it binary in order to extract the characteristics of the subject. This produces an image in which the areas where subjects exist are set to 1, and the areas where they do not exist are set to 0 and can be treated as a matrix with only 0s and 1s as elements.
This matrix can then be used to measure the number of objects by segmenting each object using kernel processing, etc.
Using packaged image processing software, a variety of processes, including these, can be performed.
In recent years, attempts have also been made to increase the accuracy of analysis and feature extraction by combining these existing image processing software with machine learning and AI technologies.
In the history of manufacturing, there has always been a need for systems that automate without human intervention, and this has evolved in the field of factory automation (FA), the automation of production processes.
In recent years, with the dramatic advances in image processing technology, the role of these systems has become increasingly important, not only in replacing workers with machines but also in production control systems to improve productivity and quality and reduce costs. Image processing systems that combine cameras and sensors with image processing equipment play a central role in this process.
Due to the global labor shortage and the growing need for safety in food and other products, inspection systems combining manpower-saving systems with image processing systems are becoming increasingly important in the automotive, food, pharmaceutical, and cosmetics-related fields. In addition, further improvements in image processing and sensor technologies have expanded the range of inspection capabilities, and the visual inspection business combining image processing systems and deep learning is gaining momentum.
One area of future focus is image sensors that utilize smartphones. With the addition of attachments and applications, smartphones can easily be used as image processing devices to read barcodes and inspect text. Since they can be easily integrated with e-commerce, they are expanding not only into the manufacturing industry but also into the logistics and retail sectors.
Image processing software used in inspection and quality control used to be developed by creating specifications and designing from system requirements when building a system, but as the processing capacity of image processing equipment has improved and the types and packages of highly versatile inspection software have become abundant, image processing software can be freely combined and used. However, as the processing capacity of image processing equipment has improved and the variety of versatile inspection software types and packages has increased, it is now possible to freely combine and utilize such software.
Packages include, for example, shape, area, color, position, and flaw determination, as well as combined length, angle, and diameter measurement software.
More recently, image processing software employing deep learning has been used to enhance recognition capabilities by allowing the software to learn in the same way as humans, and is being introduced as a replacement for tasks that were previously performed by visual inspection.
For example, it is now possible to distinguish scratches from defects in more detail, and in character recognition, it is now possible to improve the accuracy of recognition of handwritten characters.
In the field of medicine, it is now possible to detect and treat diseases that are difficult to detect with the human eye, and in the field of crime prevention, it is possible to identify individuals from images captured by security cameras.
*Including some distributors, etc.
Sort by Features
Sort by Area
This is the version of our website addressed to speakers of English in the United States. If you are a resident of another country, please select the appropriate version of Metoree for your country in the drop-down menu.