Machine vision is a combination of hardware and software that are capable of capturing and processing images in such a way that the results serve to perform some function. Typical applications of machine vision would be object recognition, event detection, scene reconstruction, or image restoration. The advances in this field are surprising, and we are getting closer to having more refined, reliable and accurate computer vision systems.
The reality is that machine vision can significantly improve safety in transportation, medicine, and many other industries. Machine vision will enhance social development by combining with advances in robotics, control technologies, artificial intelligence, and IIoT.
Applications Of Artificial Vision That Improve Our lives
- In the automotive industry, a computer vision system aids in the manufacturing process. The safety requirements in this industry are increasingly demanding, and with the advent of the autonomous car, they will be even more so. So machine vision systems can contribute to error-free and defective part production.
- By being able to monitor the manufacturing and assembly of each and every part, the increasingly powerful image processing algorithms are able to detect the smallest defects, unnoticed by the most experienced human inspector. Dents, scratches and minuscule color variations can trigger an alert during inspections, thus reducing the number of faulty vehicles hitting the market.
- In the food sector, the quality control of each type of food product will be much stricter. It will be possible to automatically control each of the phases of the product. For example, in an agricultural plantation, it will be possible to control the product in each growth phase, then control it in the harvest and the different processing phases, and even verify its integrity in transport.
- In the control of the warehouses. Thanks to artificial vision systems combined with advanced artificial intelligence algorithms, it will be possible to control stored products at all times, check their expiration date, improve rotation and achieve much greater efficiency.
- In the health sector, diagnoses may be faster, more accurate and error-free. We mention it when we discuss the advances in melanoma detection thanks to image analysis, and the same happens with the diagnosis of breast cancer.
- In addition, machine vision performs many of the functions necessary to automate clinical laboratory diagnostic tests, including detection of sample cap color, the capture of patient data from the attached barcode, and verification that Sample tubes are sufficiently full.
- The automation of routine medical tests is essential to improving patient care, shorten emergency room and increase the satisfaction of the patient and the doctor.