Soil and rock classification method and device based on image processing

Abstract

The invention discloses a soil and rock classification method and device based on image processing, and belongs to the technical field of image processing. In the design of the automatic soil and rock classification method, unsupervised clustering dichotomy is carried out on the images based on the gradient sampling duty ratio of the images, and one-time classification is completed. In soil subdivision, a soil water content detection circuit is combined, and the soil water content is used for distinguishing silty clay from plain fill. In rock subdivision, a vector profile feature set is proposed to represent the texture complexity of rock images, and unsupervised clustering dichotomy is carried out through the texture complexity to realize secondary classification of rocks; and furthermore, a profile estimation feature set is provided to represent the similarity between the shape of the object and the circle, and unsupervised clustering dichotomy is carried out to realize tertiary classification of the rock. Fine classification and identification of soil and rock can be automatically completed according to the sampling images, classification is rapid and efficient, and the requirement for hardware is low.

Description

technical field [0001] The invention relates to image processing technology, in particular to a scheme for classifying soil and rocks by using image processing technology. Background technique [0002] For the construction scene, since there are different construction methods for different geological landforms, it is necessary to first inspect and evaluate the construction environment. [0003] Initially, detection and evaluation relied on manual excavation and sampling to identify the types of environmental soil and rocks, but this method was very time-consuming and laborious, and the accuracy was not high. [0004] With the continuous update of image processing technology, the soil or rock of the sample can be more accurately identified and classified by means of image processing. However, most of the existing classification solutions use machine learning / deep learning to complete the identification of soil or rocks. For example, CN110261330A discloses a rock identificati...

AI Technical Summary

Problems solved by technology

This type of method needs to collect a huge sample set, and the category of the sample needs to be accurately defined, otherwise it will affect the classifier. In addition, this type of method requires a large amount of calculation

Moreover, most of the existing methods can only realize the identification and classification of one of soil or rock

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