Netted melon fruit phenotype extraction and quantization method

A netted melon and quantitative method technology, applied in the direction of instruments, character and pattern recognition, computer parts, etc., to achieve the effect of improving precision, improving accuracy, improving efficiency and accuracy

Active Publication Date: 2013-04-24
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

It is impossible to extract all the phenotypic parameters of reticulate melon du...

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  • Netted melon fruit phenotype extraction and quantization method
  • Netted melon fruit phenotype extraction and quantization method
  • Netted melon fruit phenotype extraction and quantization method

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Embodiment Construction

[0037] The method for extracting and quantifying reticulated muskmelon proposed by the present invention is described in detail as follows with reference to the accompanying drawings and examples. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0038] In order to quickly obtain the phenotype parameters of the reticulated muskmelon fruit, the present invention proposes a method for rapidly extracting the phenotype of the reticulated muskmelon fruit based on the RGB-D visual sensor. The method segmented the fruit of reticulated melon from the complex sub-environment, and on this basis, extracted and quantified parameters such as the vertical...

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Abstract

The invention discloses a netted melon fruit phenotype extraction and quantization method. The netted melon fruit phenotype extraction and quantization method comprises steps as follows: step 1, according to a reference substance method, a red green blue (RGB) image and a depth image of netted melon fruit is collected through a RGB-depth (D) visual sensor, and the RGB image is preprocessed; step 2, the preprocessed image is divided, a reference substance image is obtained, and the pixel length ratio is computed; step 3, the fruit is divided based on the depth image, and shape feature parameters of the fruit is obtained by computing with the pixel length ratio; step 4, outline information of the fruit obtained from the depth image is used in the RGB image to obtain a RGB image area of the fruit; step 5, according to the RGB image area of the fruit, color space switching is utilized to obtain color parameters H and S, and net characteristics of a melon is quantized based on the RGB image area and taking advantage of the net covering rate, a gray level co-occurrence matrix parameter and a polychotomy dimension parameter. By means of the netted melon fruit phenotype extraction and quantization method, extraction comprehensiveness and obtaining efficiency of netted melon phenotype are improved, and objectivity and accuracy of netted melon phenotype quantization are improved.

Description

technical field [0001] The invention relates to an objective quantification method of reticulated melon fruit phenotype, in particular to a method for extracting and quantifying the phenotype of reticulated melon fruit throughout the growth period based on RGB-D visual sensors, and in particular to a method for extracting and quantifying the phenotype of reticulated melon . Background technique [0002] Reticulated melon phenotype is an important indicator for breeding and identification of new varieties. At present, the phenotype of reticulated melon is mainly obtained by manual visual inspection and manual measurement to characterize the phenotype of reticulated melon. Visually inspect the color of the skin (whether the skin turns yellow, whether the fruit is cracked, whether the skin is double-colored), the distribution of reticulation (sparseness), whether there is wrinkled skin, and use a vernier caliper to measure the size of the vertical and horizontal diameters, etc...

Claims

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Application Information

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IPC IPC(8): G06K9/60
Inventor 黄丹枫李磊柯顺魁苗玉彬常丽英牛庆良唐东梅
Owner SHANGHAI JIAO TONG UNIV
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