Quasi-circular particulate matter counting method based on Android platform

Abstract

The invention relates to a quasi-circular particulate matter counting method based on an Android platform, and belongs to the technical field of image processing. The method comprises the following steps that: firstly, on the basis of color difference characteristics, extracting a binary image which only contains quasi-circular particulates from a background; extracting an adhesive and overlappedparticulate block area from the image, and utilizing a segmentation method based on distance transformation and H-minima to carry out first-time segmentation on the particulate block area; and puttingforward a method for accurately extracting the surface holes of the particle matter, carrying out second-time watershed segmentation on the particulate block area of which the holes are filled, removing noise and a small quality of shadow areas through connected domain analysis, solving the minimum circumcircle of the outermost layer contour of each particulate, and drawing the minimum circumcircle on an original drawing, wherein the number of circles is the number of particulates. By use of the counting system disclosed by the invention, hardware use cost is lowered, excessive segmentation and wrong segmentation brought by a traditional segmentation method are inhibited to a great extent, a great quantity of tightly adhesive single-layer particulate matters and simple two-layer quasi-circular particulate matters can be accurately detected, and high counting accuracy and counting efficiency can be obtained.

Description

technical field [0001] The invention relates to a system and method for counting round particles based on an Android platform, belonging to the technical field of image processing. Background technique [0002] In various application fields such as agriculture, industry, and medical care, it is often necessary to count the number of round particles (such as crop seeds, steel bars, cells, etc.). The traditional method is to determine the number of particles through human judgment. Since the human eye is prone to fatigue after long-term high-intensity work, the accuracy of counting is difficult to guarantee, and it is difficult to achieve manual counting in many workplaces (such as pills on the industrial assembly line, cruising in the river) duck count). With the improvement of computer technology and image processing technology, there are many researches on the automatic analysis system of quasi-circular particles based on digital image processing. number. Among them, the...

AI Technical Summary

Problems solved by technology

The traditional method is to determine the number of particles through human judgment. Since the human eye is prone to fatigue after long-term high-intensity work, the accuracy of co

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