CN116645409A - Bare soil coverage automatic detection method based on image spectrum analysis and edge detection - Google Patents
Bare soil coverage automatic detection method based on image spectrum analysis and edge detection Download PDFInfo
- Publication number
- CN116645409A CN116645409A CN202310543164.8A CN202310543164A CN116645409A CN 116645409 A CN116645409 A CN 116645409A CN 202310543164 A CN202310543164 A CN 202310543164A CN 116645409 A CN116645409 A CN 116645409A
- Authority
- CN
- China
- Prior art keywords
- bare soil
- image
- edge
- area
- bare
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 239000002689 soil Substances 0.000 title claims abstract description 151
- 238000001514 detection method Methods 0.000 title claims abstract description 41
- 238000003708 edge detection Methods 0.000 title claims abstract description 37
- 238000010183 spectrum analysis Methods 0.000 title claims abstract description 35
- 238000000605 extraction Methods 0.000 claims abstract description 24
- 238000010586 diagram Methods 0.000 claims abstract description 4
- 238000013507 mapping Methods 0.000 claims abstract description 4
- 238000004458 analytical method Methods 0.000 claims description 33
- 238000012545 processing Methods 0.000 claims description 24
- 238000000034 method Methods 0.000 claims description 19
- 238000005516 engineering process Methods 0.000 claims description 9
- 101150038863 Lsamp gene Proteins 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 5
- 230000008569 process Effects 0.000 claims description 5
- 238000001914 filtration Methods 0.000 claims description 4
- 230000002146 bilateral effect Effects 0.000 claims description 3
- 238000010276 construction Methods 0.000 description 7
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000000611 regression analysis Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 238000002310 reflectometry Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration using local operators
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
- G06T5/92—Dynamic range modification of images or parts thereof based on global image properties
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N2021/1765—Method using an image detector and processing of image signal
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
- G06T2207/20028—Bilateral filtering
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Geometry (AREA)
- Image Analysis (AREA)
Abstract
The invention provides an automatic bare soil coverage detection method based on image spectrum analysis and edge detection, which comprises the following steps: acquiring a frame extraction image of a region to be detected; inputting the frame extraction image into a pre-trained image spectrum analysis and edge detection algorithm model, and outputting to obtain edge blocks of the frame extraction image; mapping all kinds of bare soil and all kinds of bare soil covers in the edge blocks based on two specific pixel values respectively to generate a gray level map; calculating to obtain the total pixel area of the bare soil area in the gray level diagram; calculating bare soil coverage according to the total pixel area and the gray level map; and if the bare soil coverage rate is smaller than the preset threshold value, judging that the bare soil is not covered.
Description
Technical Field
The invention relates to the technical field of bare soil coverage detection in construction sites, in particular to an automatic bare soil coverage detection method based on image spectrum analysis and edge detection.
Background
Along with the gradual penetration of environmental protection into the life of people, the national requirements on construction environment are higher and higher, so strict regulations are formulated, namely, bare soil existing in a construction site during construction work needs to be covered, so that the deterioration of the construction environment caused by the existence of bare soil dust emission is avoided, the existing bare soil coverage detection method is usually realized by manual detection, the detection speed is low in a manual detection mode, and meanwhile, the detection accuracy is low, the bare soil coverage detection of a large-scale construction area is not facilitated, therefore, an automatic bare soil coverage detection method based on image spectral analysis and edge detection is needed, and an automatic mode is adopted, so that the problems of low detection speed and low detection accuracy in a manual detection mode are solved.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an automatic bare soil coverage detection method based on image spectrum analysis and edge detection, which adopts an automatic mode and is used for solving the problems of low detection speed and low detection accuracy of a manual detection mode.
A bare soil coverage automatic detection method based on image spectrum analysis and edge detection comprises the following steps: acquiring a frame extraction image of a region to be detected; inputting the frame extraction image into a pre-trained image spectrum analysis and edge detection algorithm model, and outputting to obtain edge blocks of the frame extraction image; mapping all kinds of bare soil and all kinds of bare soil covers in the edge blocks based on two specific pixel values respectively to generate a gray level map; calculating to obtain the total pixel area of the bare soil area in the gray level diagram; calculating bare soil coverage according to the total pixel area and the gray level map; and if the bare soil coverage rate is smaller than the preset threshold value, judging that the bare soil is not covered.
As an embodiment of the present invention, obtaining a frame-extracted image of a region to be detected includes: acquiring panoramic video of a region to be detected; and extracting partial video frames of the panoramic video based on a preset frame extraction interval to obtain a plurality of frame extraction images.
As an embodiment of the invention, the specific processing flow of the image spectrum analysis and edge detection algorithm model processing the frame extraction image comprises the following steps: taking the input frame extraction image as an analysis object; performing corresponding processing on the analysis object based on noise processing and brightness enhancement processing to obtain an analysis image; and identifying edge blocks of the analysis image based on an image spectrum analysis technology and an edge detection technology, and generating edge blocks containing different characteristic values, wherein each edge block corresponds to one kind of bare soil or one kind of bare soil cover.
As an embodiment of the present invention, noise processing includes: performing bilateral filtering processing on the analysis object to generate a second analysis object; the second analysis object is an image for eliminating noise, and the second analysis object holds image edge detail information.
As an embodiment of the present invention, the shading enhancement processing includes: lsamp= {0.7×lsrc, lsrc,1.3×lsrc }, where lsrc represents the original luminance of the second analysis object, and lsamp represents the luminance set of any second analysis object after luminance enhancement; and (3) at the same time of brightness adjustment, mirroring the second analysis object at random left and right or up and down.
As an embodiment of the present invention, the process flow of the edge detection technology specifically includes: the edges of bare soil and bare soil covers are detected by the method of the Sobel operator.
As an embodiment of the invention, the calculation of the total pixel area of the bare soil area in the gray scale image comprises the following steps: judging whether the gray map heavy bare soil edge range is adjacent to the bare soil covering edge range or not, and judging whether the bare soil in the corresponding area is covered by the bare soil covering or not; if the pixel areas are adjacent, calculating to obtain the sum of the pixel areas of the edge ranges of the bare soil and the bare soil cover as the total pixel area of the bare soil area; and if the pixel areas are not adjacent, calculating the pixel area of the bare soil edge range as the total pixel area of the bare soil area.
As an embodiment of the present invention, a method of calculating a pixel area of bare soil and a pixel area of a bare soil cover includes the steps of: and traversing the pixel values in the region to be detected, if the pixel value is 125, accumulating 1 in the bare soil pixel area, and if the pixel value is 255, accumulating 1 in the bare soil covering pixel area, thereby obtaining the total bare soil pixel area.
As an embodiment of the present invention, a bare soil coverage automatic detection method based on image spectrum analysis and edge detection further includes: and when calculating the bare soil coverage rate, comparing the total area pixel of each bare soil area with a preset second threshold value, and if the total area pixel of the current bare soil area is smaller than the preset second threshold value, not participating in the calculation of the bare soil coverage rate.
As an embodiment of the present invention, if the bare soil coverage is smaller than a preset threshold, determining that the bare soil is not covered includes: let bare soil coverage rmask be expressed as areacovering/areatotal; and if the bare soil is not adjacent to the bare soil covering, and the areacovering value is 0 and the bare soil coverage rate rmask is smaller than a preset threshold value, judging that the bare soil is not covered.
The beneficial effects of the invention are as follows:
the invention provides an automatic bare soil coverage detection method based on image spectrum analysis and edge detection, which adopts an automatic mode and is used for solving the problems of low detection speed and low detection accuracy of a manual detection mode.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method for automatically detecting bare soil coverage based on image spectral analysis and edge detection in an embodiment of the invention;
FIG. 2 is a flowchart of a core algorithm in an automatic bare soil coverage detection method based on image spectral analysis and edge detection in an embodiment of the present invention;
fig. 3 is a flowchart of a specific processing flow of processing a frame extraction image by using an image spectrum analysis and edge detection algorithm model in an automatic bare soil coverage detection method based on image spectrum analysis and edge detection in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Referring to fig. 1 and 2, an embodiment of the present invention provides an automatic bare soil coverage detection method based on image spectrum analysis and edge detection, including: s101, acquiring a frame extraction image of a region to be detected; s102, inputting the frame extraction image into a pre-trained image spectrum analysis and edge detection algorithm model, and outputting to obtain edge segmentation of the frame extraction image; s103, mapping all kinds of bare soil and all kinds of bare soil covers in the edge blocks based on two specific pixel values respectively to generate a gray level map; s104, calculating to obtain the total pixel area of the bare soil area in the gray level diagram; calculating bare soil coverage according to the total pixel area and the gray level map; s105, if the bare soil coverage rate is smaller than a preset threshold value, judging that the bare soil is not covered;
the bare soil cover is usually solid or has little change in overall color material, and is different from the soil which is affected by hardening, roughness and the like, so that the bare soil cover is judged in a pixel comparison mode;
the beneficial effects of the technical scheme are as follows: through above-mentioned technical scheme, adopt automatic mode, solved the mode detection speed of artificial detection slow, detect the problem that the precision is low simultaneously.
In one embodiment, acquiring a frame-extracted image of an area to be detected includes: acquiring panoramic video of a region to be detected; and extracting partial video frames of the panoramic video based on a preset frame extraction interval to obtain a plurality of frame extraction images.
Referring to fig. 3, in one embodiment, the specific processing flow of the image spectrum analysis and edge detection algorithm model to process the frame-extracted image includes: s201, taking an input frame extraction image as an analysis object; s202, correspondingly processing an analysis object based on noise processing and brightness enhancement processing to obtain an analysis image; s203, identifying edge blocks of the analysis image based on an image spectrum analysis technology and an edge detection technology, and generating edge blocks containing different characteristic values; wherein each edge segment corresponds to a bare soil or a bare soil cover.
The specific content of the image spectrum analysis is as follows: regression analysis of wavelength (lambda) and soil reflectivity (R) is carried out, and the regression analysis equation is as follows: r=aλ+b, then obtaining correlation coefficients of the two according to the correlation measurement values, and obtaining correlation coefficients of different types of bare soil approximately at about 0.9 in a wavelength interval of 0.4-1.1 um, thereby judging the bare soil according to a correlation system.
In one embodiment, the noise processing includes: performing bilateral filtering processing on the analysis object to generate a second analysis object; the second analysis object is an image for eliminating noise, and the second analysis object holds image edge detail information.
In one embodiment, the shading enhancement process comprises: lsamp= {0.7×lsrc, lsrc,1.3×lsrc }, where lsrc represents the original luminance of the second analysis object, and lsamp represents the luminance set of any second analysis object after luminance enhancement; and (3) at the same time of brightness adjustment, mirroring the second analysis object at random left and right or up and down.
In one embodiment, the process flow of the edge detection technology specifically includes: the edges of bare soil and bare soil covers are detected by the method of the Sobel operator.
In one embodiment, calculating the total pixel area of the bare soil area in the gray scale map includes: judging whether the gray map heavy bare soil edge range is adjacent to the bare soil covering edge range or not, and judging whether the bare soil in the corresponding area is covered by the bare soil covering or not; if the pixel areas are adjacent, calculating to obtain the sum of the pixel areas of the edge ranges of the bare soil and the bare soil cover as the total pixel area of the bare soil area; and if the pixel areas are not adjacent, calculating the pixel area of the bare soil edge range as the total pixel area of the bare soil area.
In one embodiment, the method for calculating the pixel area of bare soil and the pixel area of bare soil cover comprises the steps of: and traversing the pixel values in the region to be detected, if the pixel value is 125, accumulating 1 in the bare soil pixel area, and if the pixel value is 255, accumulating 1 in the bare soil covering pixel area, thereby obtaining the total bare soil pixel area.
In one embodiment, the bare soil coverage automatic detection method based on image spectrum analysis and edge detection further comprises: and when calculating the bare soil coverage rate, comparing the total area pixel of each bare soil area with a preset second threshold value, and if the total area pixel of the current bare soil area is smaller than the preset second threshold value, not participating in the calculation of the bare soil coverage rate.
It is understood that, according to the preset threshold T1 for filtering the detection area, if the total pixel area of bare soil is greater than or equal to T1, the area is the detection area, and if it is smaller than T1, the detection area is regarded as the area where no detection is performed.
In one embodiment, if the bare soil coverage is less than a preset threshold, determining that the bare soil is not covered comprises: let bare soil coverage rmask be expressed as areacovering/areatotal; and if the bare soil is not adjacent to the bare soil covering, and the areacovering value is 0 and the bare soil coverage rate rmask is smaller than a preset threshold value T2, judging that the bare soil is not covered.
According to the invention, an automatic mode is adopted, so that the problems of low detection speed and low detection accuracy of a mode for artificially detecting whether bare soil is covered in a construction area are solved, and the detection efficiency is improved and the labor cost is reduced.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. The bare soil coverage automatic detection method based on image spectrum analysis and edge detection is characterized by comprising the following steps of: acquiring a frame extraction image of a region to be detected; inputting the frame extraction image into a pre-trained image spectrum analysis and edge detection algorithm model, and outputting to obtain edge blocks of the frame extraction image; mapping all kinds of bare soil and all kinds of bare soil covers in the edge blocks based on two specific pixel values respectively to generate a gray level map; calculating to obtain the total pixel area of the bare soil area in the gray level diagram; calculating bare soil coverage according to the total pixel area and the gray level map; and if the bare soil coverage rate is smaller than the preset threshold value, judging that the bare soil is not covered.
2. The method for automatically detecting bare soil coverage based on image spectral analysis and edge detection according to claim 1, wherein obtaining a frame-extracted image of a region to be detected comprises: acquiring panoramic video of a region to be detected; and extracting partial video frames of the panoramic video based on a preset frame extraction interval to obtain a plurality of frame extraction images.
3. The method for automatically detecting bare soil coverage based on image spectral analysis and edge detection according to claim 1, wherein the specific processing flow of the image spectral analysis and edge detection algorithm model processing the frame extraction image comprises the following steps: taking the input frame extraction image as an analysis object; performing corresponding processing on the analysis object based on noise processing and brightness enhancement processing to obtain an analysis image; identifying edge blocks of the analysis image based on an image spectrum analysis technology and an edge detection technology, and generating edge blocks containing different characteristic values; wherein each edge segment corresponds to a bare soil or a bare soil cover.
4. A bare soil coverage automatic detection method based on image spectral analysis and edge detection according to claim 3, wherein the noise processing comprises: performing bilateral filtering processing on the analysis object to generate a second analysis object; the second analysis object is an image for eliminating noise, and the second analysis object holds image edge detail information.
5. A bare soil coverage automatic detection method according to claim 3, wherein the shading enhancement processing comprises: lsamp=0.7×lsrc, lsrc,1.3×lsrc }, where lsrc represents the original luminance of the second analysis object, and lsamp represents the luminance set of any second analysis object after luminance enhancement; and (3) at the same time of brightness adjustment, mirroring the second analysis object at random left and right or up and down.
6. The method for automatically detecting bare soil coverage based on image spectrum analysis and edge detection according to claim 3, wherein the process flow of the edge detection technology specifically comprises: the edges of bare soil and bare soil covers are detected by the method of the Sobel operator.
7. The method for automatically detecting bare soil coverage based on image spectral analysis and edge detection according to claim 1, wherein the calculation of the total pixel area of the bare soil area in the gray scale map comprises: judging whether the gray map heavy bare soil edge range is adjacent to the bare soil covering edge range or not, and judging whether the bare soil in the corresponding area is covered by the bare soil covering or not; if the pixel areas are adjacent, calculating to obtain the sum of the pixel areas of the edge ranges of the bare soil and the bare soil cover as the total pixel area of the bare soil area; and if the pixel areas are not adjacent, calculating the pixel area of the bare soil edge range as the total pixel area of the bare soil area.
8. The method for automatically detecting bare soil coverage based on image spectral analysis and edge detection according to claim 7, wherein the method for calculating the pixel area of bare soil and the pixel area of bare soil coverage comprises the steps of: and traversing the pixel values in the region to be detected, if the pixel value is 125, accumulating 1 in the bare soil pixel area, and if the pixel value is 255, accumulating 1 in the bare soil covering pixel area, thereby obtaining the total bare soil pixel area.
9. The method for automatically detecting bare soil coverage based on image spectral analysis and edge detection according to claim 1, further comprising: and when calculating the bare soil coverage rate, comparing the total area pixel of each bare soil area with a preset second threshold value, and if the total area pixel of the current bare soil area is smaller than the preset second threshold value, not participating in the calculation of the bare soil coverage rate.
10. The method for automatically detecting bare soil coverage based on image spectral analysis and edge detection according to claim 1, wherein if the bare soil coverage is smaller than a preset threshold, determining that the bare soil is not covered comprises: let bare soil coverage rmask be expressed as areacovering/areatotal; and if the bare soil is not adjacent to the bare soil covering, and the areacovering value is 0 and the bare soil coverage rate rmask is smaller than a preset threshold value, judging that the bare soil is not covered.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310543164.8A CN116645409A (en) | 2023-05-15 | 2023-05-15 | Bare soil coverage automatic detection method based on image spectrum analysis and edge detection |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310543164.8A CN116645409A (en) | 2023-05-15 | 2023-05-15 | Bare soil coverage automatic detection method based on image spectrum analysis and edge detection |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116645409A true CN116645409A (en) | 2023-08-25 |
Family
ID=87623965
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310543164.8A Pending CN116645409A (en) | 2023-05-15 | 2023-05-15 | Bare soil coverage automatic detection method based on image spectrum analysis and edge detection |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116645409A (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112215815A (en) * | 2020-10-12 | 2021-01-12 | 杭州视在科技有限公司 | Bare soil coverage automatic detection method for construction site |
| CN113627388A (en) * | 2021-08-30 | 2021-11-09 | 浙江大华技术股份有限公司 | Method and device for determining bare soil coverage condition |
-
2023
- 2023-05-15 CN CN202310543164.8A patent/CN116645409A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112215815A (en) * | 2020-10-12 | 2021-01-12 | 杭州视在科技有限公司 | Bare soil coverage automatic detection method for construction site |
| CN113627388A (en) * | 2021-08-30 | 2021-11-09 | 浙江大华技术股份有限公司 | Method and device for determining bare soil coverage condition |
Non-Patent Citations (1)
| Title |
|---|
| 温小乐 等: "基于光谱分析的平潭综合实验区建设初期裸土变化的遥感监测", 《福州大学学报(自然科学版)》, vol. 44, no. 01, pages 52 - 56 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111612757B (en) | Screen crack detection method, device, equipment and storage medium | |
| CN108550159B (en) | Flue gas concentration identification method based on image three-color segmentation | |
| CN111060521B (en) | Method for detecting quantity and area of air bubbles on surface of precast concrete T beam | |
| CN102175700A (en) | Method for detecting welding seam segmentation and defects of digital X-ray images | |
| CN109800654B (en) | Vehicle-mounted camera detection processing method and device and vehicle | |
| CN111489352A (en) | Tunnel gap detection and measurement method and device based on digital image processing | |
| CN112669301B (en) | High-speed rail bottom plate paint removal fault detection method | |
| CN111767874B (en) | Pavement disease detection method based on deep learning | |
| CN110807406B (en) | Foggy day detection method and device | |
| CN113487563B (en) | EL image-based self-adaptive detection method for hidden cracks of photovoltaic module | |
| CN113658345A (en) | Sample labeling method and device | |
| CN113284113A (en) | Glue overflow flaw detection method and device, computer equipment and readable storage medium | |
| CN115861315B (en) | Defect detection method and device | |
| CN117115171A (en) | Slight bright point defect detection method applied to subway LCD display screen | |
| CN110428411B (en) | Backlight plate detection method and system based on secondary exposure | |
| CN116645409A (en) | Bare soil coverage automatic detection method based on image spectrum analysis and edge detection | |
| CN115690089A (en) | Image enhancement preprocessing method and system for weak defect detection | |
| CN114638822B (en) | Method and system for detecting surface quality of automobile cover plate by using optical means | |
| CN116228659A (en) | Visual detection method for oil leakage of EMS trolley | |
| CN110634124A (en) | Method and equipment for area detection | |
| CN110798680B (en) | Single-frame no-reference self-adaptive video snowflake noise detection method | |
| CN114005036A (en) | Bare soil monitoring and early warning method and device, computer equipment and storage medium | |
| CN114359166A (en) | Screen color detection method, device, equipment and storage medium | |
| CN110751618B (en) | Floater detection method and device and electronic equipment | |
| CN110322431B (en) | Haze image quality evaluation method and system, storage medium and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |