Image Energy Saving Recognition Technology of Monitoring System Based on Ant Colony Algorithm

Abstract

In order to solve the shortcomings of traditional monitoring and alarm system, the key technology of intelligent video monitoring system-image processing and recognition technology is studied. The image energy-saving recognition technology of monitoring system based on ant colony algorithm is proposed. The ant colony algorithm is used to segment the image, extract the suspicious area, and then deal with the suspicious area separately by using the reasoning based on default rules in artificial intelligence. Using the trained neural network, the recognition experiment is carried out on 40 samples, and the recognition accuracy is more than 93%, which shows that it is very effective to use 7 invariant moments in the target image area as the characteristic parameters of target recognition. The microcomputer 2 renewal for a single target area is identified by using a moment invariant calculation force method and neural network. The execution time of the test on the microcomputer of Saijie 1.0 is microsecond. The experiment proves that it is practical and reliable, meets the real-time requirements, and can transmit the alarm signal and suspicious area image to the alarm center through the network.

An Improved Model of Product Classification Feature Extraction and Recognition Based on Intelligent Image Recognition

“…In the 1960s, the study of machine vision recognition evolved from two-dimensional to three-dimensional. First, American professors believed that, just as polygons can be understood by breaking them into triangles of different sizes, if images of physical objects are taken and processed by a computer program and broken down into more easily understood and analyzed basic three-dimensional structures such as cubes, spheres, cylinders, and vertebrae, and their coordinates and dimensions are described in mathematical language, and if simple regular three-dimensional structures can be extended to more complex three-dimensional structures, machine stereo vision recognition will have a wider application [ 5 ]. The above is the theoretical basis for the gradual introduction of machine vision into manufacturing work.…”