Image recognition method of coal and gangue

Abstract

An image recognition method of coal and gangue is disclosed. According to differences of gray scales and textures of coal and gangue surfaces, through using a computer image processing technology, 5 characteristic parameters of a gray histogram of coal and gangue images and 11 characteristic parameters of a gray level co-occurrence matrix are extracted respectively, totaling 16 characteristic parameters. A BP neural network algorithm is used to identify the coal and the gangue and process the coal and gangue images. The computer is used to carry out intelligent identification and sorting. In a trained BP neural network, any one of the characteristic parameters extracted from the coal or gangue digit images is input so that an identification result can be obtained from an output layer. The method is beneficial to sort the coal and the gangue. Coal quality can be increased. A recognition rate is high and operation is easy.

Description

technical field [0001] The invention relates to an image recognition method, in particular to a computer-based automatic image recognition method for coal and gangue. Background technique [0002] In the process of coal production and processing, a large amount of gangue will be produced. The traditional separation methods such as dense medium method and jigging method have huge equipment and serious water pollution, which will cause great harm to the health of workers and the environment. Therefore, modern automatic Sorting equipment is very necessary. The premise of manufacturing automatic sorting equipment is to find the significant difference between coal and gangue. Among the currently disclosed separation methods, the most important one is the coal and gangue separation method based on gamma ray and dual-energy gamma ray detection technology. At present, there are roughly two types of coal and gangue separation based on image processing, one One is the recognition me...

AI Technical Summary

Problems solved by technology

Among the currently disclosed separation methods, the most important one is the coal and gangue separation method based on gamma ray and dual-energy gamma ray detection technology. At present, there are roughly two types of coal and gangue separation based on image processing, one One is the recognition method based on the gray histogram of the image, and the other is the recognition method based on the image gray co-occurrence matrix, but its recognition rate is low

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