Method for automatically extracting area-of-interest from hyperspectral image of green soybeans based on iteration threshold value

Abstract

The invention relates to a method for automatically extracting an area-of-interest from a hyperspectral image of green soybeans based on an iteration threshold value. The method can be used for automatically extracting the area-of-interest of the green soybeans. According to the technical scheme, the method comprises the following steps: a, partitioning an image under a wave band with the highest transmissivity into two parts, namely a background and the green soybeans, according to a primary threshold value estimation value, calculating an average grey value of the two parts, and calculating a new threshold value according to the average grey value until the current calculated threshold value is equal to the previous threshold value; b, finding out the coordinates of the background in order to enhance the contrast, assigning the grey value of the background into 255, and keeping the grey value of the green soybeans unchanged; c, binarizing the image by threshold value partitioning to partition pods and pisolites; d, mapping the coordinates of the pisolites, namely the area-of-interest, to other wave bands to obtain the area-of-interest under the full wave band. By automatic extraction of the area-of-interest of the green soybeans and combination of a classification pre-estimation model and a hyperspectral image acquisition system, a detection result of bean-pod borers of the green soybeans is obtained; the method is high in real-time performance, time-saving, labor-saving and high in reliability.

Description

technical field [0001] The invention relates to a method for extracting a region of interest in a hyperspectral image of the edamame pod borer, in particular to a method for non-destructive detection of the hyperspectral image of the edamame pod borer by using an automatic method to extract the region of interest. Background technique [0002] Edamame, because of its delicious taste and rich nutrition, is widely loved by people all over the world. With the improvement of living standards, the safety of edamame has become an indicator that consumers and manufacturers are quite concerned about. Bean pod borer is one of the main pests of beans. It parasitizes soybeans when they are young and eats beans for a living. However, the gnawed soybeans lose their use value. strict requirements have been put forward. At present, manual destructive observation and detection are basically used in the detection of pod borer in edamame. Although more and more scholars apply non-destructiv...

AI Technical Summary

Problems solved by technology

In the past, the region of interest of edamame was extracted manually by manual software, which had the disadvantages of strong dependence on personnel, incomplete extraction of region of interest, time-consuming and labor-intensive, and difficult real-time online application.

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