Rice grain segmentation method, terminal and storage medium

Abstract

The invention discloses a rice grain segmentation method, a terminal and a storage medium, and the method comprises the steps: carrying out the noise reduction and binarization of a collected rice grain image, carrying out the connected region detection of an obtained binarized image after noise reduction, and obtaining a connected region; according to a preset threshold value and the perimeter and the area corresponding to the communication area, dividing the communication area into an adhesion rice area or a single-grain rice area; obtaining a candidate clustering center pixel point in the adhesion meter area according to the coordinate value of each pixel point in the adhesion meter area and a density peak clustering algorithm; training a preset Gaussian mixture model according to an EMalgorithm, a contour coefficient algorithm, the coordinate value of each candidate clustering center pixel point in the adhesion meter area and the coordinate values of other pixel points to obtain an optimized Gaussian mixture model; and carrying out rice grain segmentation on the adhesion rice area according to the optimized Gaussian mixture model to obtain a segmentation result of the adhesionrice area. According to the invention, the problem of poor segmentation quality of the rice grain image in the existing adhesion object segmentation method is solved.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for segmenting rice grains, a terminal and a computer-readable storage medium. Background technique [0002] When collecting rice grain images in batches, due to the lack of constraints on the placement of rice grains, the collected rice grain images not only have the form of a single grain of rice, but also have the situation of rice grains sticking together, which will affect the shape of the subsequent rice grains Indicator calculation. This requires the use of image processing methods to segment the cohesive particles. [0003] The image processing methods used in the existing literature to segment cohesive objects mainly include the watershed algorithm and the pit detection algorithm. The watershed algorithm simulates the idea of ​​watershed dam swelling to form a dividing line at the junction of each area, but it is easily affected by noise, which is prone to over...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to propose a method for segmenting rice grains, a terminal and a computer-readable storage medium, aiming to solve the problem of poor segmentation quality of rice grain images in existing image processing methods for segmenting sticky objects

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