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Sugarcane characteristic extraction and recognition method based on computer vision

A technology of computer vision and feature extraction, applied in the field of image processing

Inactive Publication Date: 2013-02-20
汪建
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Problems solved by technology

At present, domestic research in this field is still blank

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  • Sugarcane characteristic extraction and recognition method based on computer vision
  • Sugarcane characteristic extraction and recognition method based on computer vision
  • Sugarcane characteristic extraction and recognition method based on computer vision

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Experimental program
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Embodiment Construction

[0046] Extract 50 pictures of sugarcane from the collected images and combine them with the training library for testing. After basic image processing, extract 50 images, each with 64 columns and blocks, a total of 3200 samples, and calculate the feature indicators of each sample; through the method of manual identification, classify the category attributes of 3200 samples. In the statistics, it is found that since the block ratio of internodes and stem nodes in an image reaches 10:1, it is necessary to extract training samples with a similar ratio between classes to train the model, so all stem nodes are extracted from the samples. A total of 800 samples and some internode samples were used to establish a classification model. In SVM, set C=20, G=0.01 through crossover experiment.

[0047] The implementation steps of SVM recognition:

[0048] (1) Obtain the stem nodes identified by the SVM, calculate the number Nm of stem node blocks, and take the position distance between ...

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Abstract

The invention adopts the computer vision technology to recognize characteristics of shapes and nodes of sugarcanes for achieving growth monitoring of the sugarcanes or intelligent segmentation of sugarcane varieties containing sugarcane shoots. Firstly, sugarcane images are obtained through a digital device, S components in a hue saturation value (HSV) color space of the sugarcane images are processed through threshold segmentation and mathematical morphology filter to be used as a template, reserve images of H components are segmented by threshold and calculation to obtain a composite image, the composite image is divided into 64 column areas, characteristic index of mass center ratio, roughness ratio, white spot ratio and the like is extracted, the nodes and internode columns are classified and recognized through a support vector machine so as to obtain the relation of the nodes and positions, and the average recognition rate is 93.71%.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a method for extracting and recognizing sugarcane features combined with sugarcane images and calculation models. Background technique [0002] During the growth and post-processing of sugarcane, the growth state and the cutting of sugarcane buds have been done manually for a long time. This method can automatically recognize the image of sugarcane through the identification and processing of computer vision technology. During the treatment, the whole sugarcane needs to be cut into effective sugarcane fragments containing 1 to 3 cane buds. At present, it is mostly done manually. In order to improve efficiency, reduce labor intensity and realize the refinement of sugarcane planting, it is necessary to develop an intelligent cutting device that can identify stem nodes and internodes, and the most critical thing is to identify sugarcane stem nodes. At present, domestic rese...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/66
Inventor 汪建
Owner 汪建
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