Multi-resolution visual identification method for grain insect species

Abstract

The invention discloses a multi-resolution visual identification method for grain insect species. The method comprises steps as follows: three shot grain insect images with low resolution, medium resolution and high resolution are binarized with an OTSU algorithm respectively, connected regions of the grain insect images with low resolution, medium resolution and high resolution are extracted witha Blob algorithm, and a suspected grain insect target area is positioned in the grain insect image with low resolution; reverse positioning is performed according to magnification of the images withmedium resolution and low resolution and the suspected grain insect target area in the grain insect image with low resolution, area parameters and perimeter parameters are calculated, and whether thesuspected grain insect target area is a grain insect area is determined; finally, on the basis of the connected region, extracted with the Blob algorithm, of the image with high resolution, reverse positioning is performed according to magnification of the images with high resolution and medium resolution and the determined medium-resolution grain insect area, and grain insect identification is realized by a random forest classifier according to LBP (local binary pattern) grain insect texture characteristics. The grain insect species are identified efficiently and accurately by the aid of advantages of development tools and image processing algorithms.

Description

technical field [0001] The invention relates to the field of detection of stored grain conditions, in particular to a multi-resolution visual recognition method for grain insect species. Background technique [0002] Maintaining a certain amount, variety and quality of grain reserves is an important measure to ensure national food security. Among them, the harm of stored grain pests has been one of the more prominent problems in this field for a long time. Grain insect identification is an effective means of grain insect integrated control. The main methods are sampling method, trapping method, voice recognition method, near-infrared method and visual detection method. Since the American scholar Zayas used vision technology to conduct offline research on the grain beetle adults in bulk wheat bins, it has opened up a new way for the rapid detection and classification of grain insects. The visual recognition method has the advantages of high accuracy, less labor, visualizat...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a multi-resolution visual identification method for grain insect species, so as to solve the problem that the existing grain insect visual detection method cannot overcome the influence of the actual granary storage composite environment

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