Sugarcane segmentation and recognition method based on computer vision

A technology of computer vision and recognition methods, applied in the field of image processing

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

Domestic research on automatic recognition technology of sugarcane stem images has not been reported yet

Method used

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  • Sugarcane segmentation and recognition method based on computer vision
  • Sugarcane segmentation and recognition method based on computer vision
  • Sugarcane segmentation and recognition method based on computer vision

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Experimental program
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Embodiment Construction

[0046] Extract 50 sugarcane pictures from the collected images combined with the training library for testing. After basic image processing, 50 images were extracted, each with 64 column blocks, a total of 3200 samples, and the characteristic indexes of each sample were calculated; after manual identification method, the category attributes of 3200 samples were divided. It is found in statistics that because the ratio of internodes to stem nodes in an image reaches 10:1, it is necessary to extract training samples with the same ratio between classes to train the model, so all stem node samples are extracted from the samples. A total of 800 samples of inter-nodal classes are used to establish a classification model. In SVM, C=20 and G=0.01 are set after cross-examination.

[0047] Implementation steps of SVM recognition:

[0048] (1) Obtain the stem nodes identified by SVM, calculate the number Nm of stem nodes, and use the distance between the stem nodes as the characteristic par...

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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, hue saturation intensity (HSI) color space conversion is performed on the sugarcane images, color characteristics and threshold segmentation of an H component and an S component are combined, reverse images are segmented by threshold and calculation to obtain a composite image, the composite image is divided into 64 column areas, finally characteristic index of H parameters, S parameters, 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 complete recognition of the nodes and positions, and average recognition rate is 94.2%.

Description

Technical field [0001] The invention belongs to the technical field of image processing, and is a method for extracting and recognizing sugarcane characteristics by combining sugarcane images and calculation models. Background technique [0002] In the process of sugarcane growth and post-processing, the growth state and the cutting of sugarcane buds have been manually completed for a long time. This method can automatically identify the image of sugarcane through the recognition and processing of computer vision technology. It is necessary to cut the whole root sugarcane into effective sugarcane seed fragments containing 1 to 3 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 important thing is to identify sugarcane stem nodes. At present, domestic research in th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/60G06K9/66
Inventor 汪建
Owner 汪建
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