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Research on classification and identification of library based on artificial intelligence

With the popularization of open borrowing, it is urgent for major libraries to explore new collection classification and identification systems to assist or replace librarians in their daily book cataloguing work. The messy books can be marked according to invisible colors, which puts forward a new method of library classification. In the algorithm used to detect image edges, by looking for the traditional sensitivity measurement system, the best parameters are applied to the wrong book image edges, and the test results are verified to find the best parameter range. A two-dimensional algorithm is used to segment the information element matrix to reduce sound. The results show that the image edge test is effective and reduces the influence of noise on the image test. The self-adjustment control algorithm of a single neuron is used to control the robot orbit, which makes the robot not only react quickly, but also reduce a small part of the error in meeting the actual needs of the robot. The effect on the result is getting smaller and smaller.