Purple Soil Image Segmentation and Extraction Method Based on Adaptive Density Peak Clustering

Abstract

The present invention provides a method for segmenting and extracting purple soil images based on adaptive density peak clustering, the method comprising the following steps: S1: performing separable grayscale transformation on purple soil color images containing purple soil regions to obtain grayscale Image Ⅰ; ​​S2: Preliminary segmentation of gray image Ⅰ by adaptive density peak clustering algorithm to obtain binary image Ⅱ after preliminary segmentation; S3: Boundary extraction processing of binary image Ⅱ to obtain the boundary of purple soil area Matrix; S4: Fill the extracted boundary matrix to obtain binary image III; S5: Find the Hadamard product of binary image III and the color image containing the purple soil area, and obtain the segmentation that only contains the purple soil image image. The application can accurately and completely segment the image of the purple soil area from the background, and realize the adaptive segmentation of the purple soil during the segmentation process, which has the beneficial technical effect of fast, accurate and complete segmentation.

Description

technical field [0001] The invention relates to an image segmentation and extraction method, in particular to a purple soil image segmentation and extraction method based on adaptive density peak clustering. Background technique [0002] With the continuous development of artificial intelligence technology, it has been widely used in many fields of production and life; in many branches of artificial intelligence, machine vision has developed rapidly. In short, machine vision is to replace human eyes with machines. measure and judge. In agricultural production, the identification of soil species and soil genus is completely dependent on agricultural experts. As we all know, soil identification is very important in agricultural production, because soil identification requires high professional skills of identifying people, such as existing The identification of soil species and soil genus is completely dependent on agricultural experts, which hinders the popularization of soi...

AI Technical Summary

Problems solved by technology

Machine vision soil recognition is to identify soil images with complex backgrounds taken under natural conditions in the field and accurately determine the soil type of the soil. However, the color images of purple soil taken in natural environments generally contain crops, lichens, mosses, Complex backgrounds such as grass will interfere with machine vision recognition

Images