Lab color space algorithm-based moss coverage degree extracting method

A technology of color space and coverage, applied in computing, image data processing, instruments, etc., can solve problems such as no relevant research on bryophyte extraction, achieve the effects of reducing manual operations, improving extraction accuracy, and improving efficiency

Inactive Publication Date: 2017-01-04
HANGZHOU NORMAL UNIVERSITY
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Problems solved by technology

Existing research on vegetation coverage based on digital photos is mainly aimed at the extraction of rice, corn and other crops and grassland, and there is no related research on the extraction of bryophytes.

Method used

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  • Lab color space algorithm-based moss coverage degree extracting method
  • Lab color space algorithm-based moss coverage degree extracting method
  • Lab color space algorithm-based moss coverage degree extracting method

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Embodiment Construction

[0022] The present invention will be further described below in conjunction with the accompanying drawings

[0023] figure 1 It is a schematic diagram of the technical route of the classification method of the present invention. By analyzing the color characteristics of bryophytes, the red and green components (a*) of the Lab color space are used to extract the moss coverage in the digital photo. First, convert the RGB color space of the acquired digital photo of moss to Lab color space; second, according to the color characteristics of the moss on the digital photo, use the red and green components (a*) of the Lab color space to extract the moss by setting the gray value threshold Coverage: Finally, convert the extracted moss and non-moss (background) parts into binary values ​​and count the number of pixels to calculate the moss coverage.

[0024] Digital photos have 3 different colors. Each color corresponds to a different spectrally sensitive band in visible light. The three ba...

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Abstract

The invention discloses a Lab color space algorithm-based moss coverage degree extracting method. The method includes the following steps that: the RGB color space of an acquired moss digital photo is converted into a Lab color space; according to the color characteristics of mosses in the digital photo, gray threshold values are set through using the red and green components of the Lab color space, so that a moss area can be extracted out; and the number of pixels of the moss area is obtained, the ratio of the number of the pixels of the moss area to the total number of the pixels of the photo is calculated, so that the coverage degree of the mosses can be obtained. With the method adopted, the defect that the colors of plants are varied which is caused by the mixing of green and red mosses in different growing stages of the mosses can be eliminated; influence on classification caused by other colors can be avoided; the coverage degree of the mosses can be better extracted; and the extraction precision of the mosses can be effectively improved.

Description

Technical field [0001] The invention relates to a method for obtaining moss coverage, in particular to a method for extracting moss coverage based on Lab color space algorithm, and relates to the fields of computer image processing and ecology. Background technique [0002] At present, in the research of vegetation coverage information extraction, the method of using computer digital image processing is one of the more common methods, and it is simple and easy to implement. The traditional method of extracting moss coverage is grid estimation method, which divides the study plot into a number of squares of equal area, which is directly judged by the naked eye based on experience, and then estimates the vegetation coverage of the squares, and finally takes the average value as the study sample The vegetation coverage of the land. Generally, a 0.5m*0.5m sampling frame is used to select the moss area. There are 26*26 intersections in the frame. The vegetation coverage of the study ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/60G06T7/00
CPCG06T2207/10024G06T2207/30004
Inventor 王甜甜徐俊锋蔡占庆刘光吴玉环
Owner HANGZHOU NORMAL UNIVERSITY
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