Fogdrop sample image processing method in camera

Abstract

The invention discloses a fog drop sample image processing method in a camera, and relates to the field of spray quality detection. The method comprises the following steps: collecting a sample imageuniformly irradiated by a light source; intercepting a sampling image with uniform brightness from the sample image; carrying out bilateral filtering noise reduction and graying processing on the sampled image; correcting the distortion of the grayed image; carrying out adhesion fog drop judgment on the corrected image; fully segmenting and marking the judged adhered fog drops by adopting a morphological opening operation segmentation method; separating and counting the fog drops by using a watershed segmentation method, binarizing the corrected grayscale images, classifying and summing the binary images to obtain the total number of pixel points of the fog drops and the total number of pixel points of the sampled images, and substituting the total number into a formula to calculate a spray quality parameter. The problems that in the prior art, an instrument is heavy, a fogdrop image segmentation algorithm is inaccurate, and noise pixel points reduce result accuracy are solved. The method can be widely applied to real-time analysis of spraying quality in severe field environments.

Description

technical field [0001] The invention relates to the field of spray quality detection, in particular to an image processing method of a droplet sample in a camera. Background technique [0002] In order to improve the accuracy of agricultural pesticide application, control the cost of pesticide application, and reduce pesticide residues in agricultural production, the usual method of spraying pesticides is to atomize pesticides to achieve the purpose of uniform spraying and precise spraying, while the uniformity of spraying is Relying on the experience of farmers to judge, the scientific nature is too low and the accuracy is not high, so the spray quality analysis is particularly important. [0003] At present, most of the existing spray quality analysis methods rely on the water-sensitive characteristics of the water-sensitive test paper to calculate and analyze the total number of droplets and the total area of ​​the droplets on the water-sensitive test paper after spraying...

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Problems solved by technology

[0005] In view of the above situation, in order to overcome the defects of the prior art, the object of the present invention is to provide a method for image processing of the fog droplet sample in the camera, which has the characteristics of comprehensive consideration and humanized operation design, and solves the problem of the segmentation of the sticky fog droplets in the prior art. Large errors, bulky instruments and the influence of noise pixels on the measurement results

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