Disease spot image segmentation method and system for greenhouse vegetable leaf

Abstract

The invention provides a disease spot image segmentation method and system for a greenhouse vegetable leaf. The method comprises: vegetable leaf disease-spot images collected at a greenhouse field are divided into a training set and a testing set and enhancement processing is carried out on the images; initial color classification features and gradient features of the training set images after enhancement processing are extracted; the training set images after enhancement processing are classified into disease spot samples and leaf samples, and initial color classification feature data and gradient feature data of the disease spot samples and the leaf samples are obtained based on the extracted initial color classification features and gradient features; with a rough set method, color classification features are selected for the initial color classification feature data of the disease spot samples and leaf samples, thereby obtaining a color feature set; according to the color feature set and the gradient feature data of the disease spot samples and leaf samples, a condition random field model is constructed; and on the basis of the condition random field model, the testing set images after enhancement processing are segmented and disease-spot images are extracted. According to the invention, a disease-spot image can be extracted accurately and the speed is fast.

Description

technical field [0001] The invention relates to the fields of system engineering and information technology, in particular to a method and system for segmenting images of lesion spots on vegetable leaves in facilities. Background technique [0002] At present, image segmentation has been a research hotspot in the field of computer vision and image processing. The so-called image segmentation is the process of dividing an image into non-overlapping and similar feature regions, and then extracting the region of interest from multiple regions. Disease spot segmentation is the most important part of crop disease detection based on computer vision technology, and it is the basic step of disease spot feature extraction and selection. Therefore, accurate disease spot segmentation is of great significance for the accurate identification of vegetable diseases. [0003] At present, there are many image segmentation algorithms, mainly including the following: (1) The threshold-based ...

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Problems solved by technology

(4) The active contour model segmentation method can be divided into parametric active contour model and geometric active contour model. Although it can achieve better segmentation effect, this method is more complicated and has a large amount of calculation. It is difficult to meet real-time requirements. Require

[0004] Since the lesion image of greenhouse leafy vegetables is collected under the conditions of the greenhouse, and through analysis, it is found that the number of lesion is large, the area is small, and its color feature is not the dominant color feature of the entire image, so it is difficult to locate the lesion by an automatic method. spot location

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