An image recognition system and picking method for intelligent picking of ores

Abstract

The invention discloses an image recognition system and a picking method for intelligent picking of ores, including an image recognition module, a display terminal, a control terminal and an external rejecting device. Module connection, described image recognition module comprises parallel data interface circuit, signal analysis and processing circuit, VGA signal output circuit, system control circuit, SPP‑16 digital interface circuit, power supply circuit, described parallel data interface circuit, VGA signal output Circuit, system control circuit, SPP‑16 digital interface circuit are all connected with the signal analysis and processing circuit, the image recognition system and picking method for ore intelligent picking of the present invention have self-learning characteristics, and have strong flexibility for ore image characteristics Applicability meets the characteristic requirements of large differences in ore shapes and a wide range of color distribution.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to an image recognition system and a sorting method for intelligent ore sorting. Background technique [0002] Image recognition technology is an important field of artificial intelligence. Based on the main features of the image, it uses pattern recognition, template matching or prototype matching to identify and process images, and the technology of using color features for recognition and processing has been successfully applied. To the field of grain sorting and processing such as rice and miscellaneous grains. [0003] There are many sorting methods for ore, and the methods usually selected in combination with ore characteristics include gravity separation, magnetic separation and flotation, etc.; There are differences in image characteristics among them, so image recognition technology can be used to sort them, which can achieve a better sorting effect of coarse-gra...

AI Technical Summary

Problems solved by technology

[0003] There are many sorting methods for ore, and the methods usually selected in combination with ore characteristics include gravity separation, magnetic separation and flotation, etc.; There are differences in image characteristics among them, so image recognition technology can be used to sort them, which can achieve a better sorting effect of coarse-grained ore pre-selection, tailing, and impurity removal; existing grain color sorters face differences in the shape of ore particles The characteristics of large size and wide distribution of color features cannot fully meet its use requirements, so it is necessary to design according to the characteristics of ore, and develop image recognition circuits and software processing methods that meet its sorting requirements

Images