What is the future of machine vision?

In the current era of intelligent manufacturing industry 4.0 with high-end equipment manufacturing as the core, with the deepening of the "Made in China 2025" strategy, the intelligent industrial robot industry market presents a growing momentum, among which the machine vision inspection as the industrial robot's eyes and golden eyes role has played an indispensable role.

Taking the current security industry as an example, the technology of security has been evolving. When network and high definition are completed, intelligent application becomes a popular technology among various security manufacturers. It should be said that since 2012, the security industry has launched in-depth research and development and discussion on how to make products and systems intelligent application, which has triggered a wave of technology trends. If intelligent video analysis is the 2.0 version of intelligent security application, then machine vision detection will open the 2.0 era of intelligent security application.

In the future, machine vision detection is a branch of AI artificial intelligence that is developing rapidly. Simply put, machine vision is to use machines instead of human eyes to make measurements and judgments. By means of a sub-CMOS or CCD sensor, the captured object is converted into an image signal, which is sent to a special image processing system, and the morphology information of the captured object is obtained. According to the pixel distribution, brightness, color and other information, it is converted into a digital signal. The image system performs various operations on these signals to extract the features of the target, and then controls the equipment action in the field according to the discriminant results.

Machine vision detection is mainly for image recognition, so machine vision has been widely used in face recognition, license plate recognition and so on. Take intelligent transportation industry as an example, machine vision has the advantages of low cost, strong stability, high accuracy, wide range of applications, and so on. At present, it has been widely used in the traffic monitoring system of highways and highways at home and abroad, which is embodied in license plate recognition, body color recognition, vehicle identification, violation recognition, traffic flow statistics, flow control, etc., in industrial applications, There are also visual dispensing machine, visual robot and a series of equipment, for the majority of business owners open source and throttle up a great help.

At this point, some people will wonder whether machine vision and deep learning have too much overlap, and whether they are different expressions of the same concept in the security industry. In fact, if only from the video surveillance industry, the learning algorithm is a higher level of machine vision application, because based on a huge sample collection to grasp the characteristics of a large number of data, and machine vision is mainly in feature perception, image preprocessing, feature extraction, feature screening surface is good at, that is to say, machine vision is mainly in the feature recognition refining part, Deep learning, on the other hand, combines features with learning. For example, feature perception and extraction are used to predict data, so that various emergencies can be predicted in advance.