CN113763357A - 基于可见光影像的矿区地裂缝精准识别与连续提取方法 - Google Patents
基于可见光影像的矿区地裂缝精准识别与连续提取方法 Download PDFInfo
- Publication number
- CN113763357A CN113763357A CN202111048411.4A CN202111048411A CN113763357A CN 113763357 A CN113763357 A CN 113763357A CN 202111048411 A CN202111048411 A CN 202111048411A CN 113763357 A CN113763357 A CN 113763357A
- Authority
- CN
- China
- Prior art keywords
- ground
- crack
- extraction
- image
- growth
- 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.)
- Granted
Links
- 238000000605 extraction Methods 0.000 title claims abstract description 129
- 238000005065 mining Methods 0.000 title claims abstract description 21
- 230000012010 growth Effects 0.000 claims abstract description 107
- 230000011218 segmentation Effects 0.000 claims abstract description 67
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 42
- 238000000034 method Methods 0.000 claims abstract description 35
- 238000012216 screening Methods 0.000 claims abstract description 29
- 238000003708 edge detection Methods 0.000 claims abstract description 18
- 230000002093 peripheral effect Effects 0.000 claims abstract description 10
- 238000005516 engineering process Methods 0.000 claims abstract description 7
- 230000003595 spectral effect Effects 0.000 claims description 26
- 230000000694 effects Effects 0.000 claims description 19
- 238000003709 image segmentation Methods 0.000 claims description 19
- 230000000877 morphologic effect Effects 0.000 claims description 15
- 238000004458 analytical method Methods 0.000 claims description 13
- 238000001228 spectrum Methods 0.000 claims description 8
- 238000001514 detection method Methods 0.000 claims description 6
- 230000007613 environmental effect Effects 0.000 claims description 4
- 230000001105 regulatory effect Effects 0.000 claims description 4
- 230000002708 enhancing effect Effects 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 238000007670 refining Methods 0.000 claims description 2
- 239000007787 solid Substances 0.000 claims description 2
- NQLVQOSNDJXLKG-UHFFFAOYSA-N prosulfocarb Chemical compound CCCN(CCC)C(=O)SCC1=CC=CC=C1 NQLVQOSNDJXLKG-UHFFFAOYSA-N 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 14
- 238000009826 distribution Methods 0.000 description 13
- 239000000284 extract Substances 0.000 description 7
- 230000000007 visual effect Effects 0.000 description 6
- 238000005070 sampling Methods 0.000 description 5
- 238000011156 evaluation Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 238000012935 Averaging Methods 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000005755 formation reaction Methods 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000035040 seed growth Effects 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 241000196324 Embryophyta Species 0.000 description 1
- 238000009412 basement excavation Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 239000003245 coal Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 238000011158 quantitative evaluation Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- 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
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/12—Edge-based segmentation
-
- 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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
-
- 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
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Quality & Reliability (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
Description
Claims (7)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111048411.4A CN113763357B (zh) | 2021-09-08 | 2021-09-08 | 基于可见光影像的矿区地裂缝精准识别与连续提取方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111048411.4A CN113763357B (zh) | 2021-09-08 | 2021-09-08 | 基于可见光影像的矿区地裂缝精准识别与连续提取方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113763357A true CN113763357A (zh) | 2021-12-07 |
CN113763357B CN113763357B (zh) | 2023-11-28 |
Family
ID=78793756
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202111048411.4A Active CN113763357B (zh) | 2021-09-08 | 2021-09-08 | 基于可见光影像的矿区地裂缝精准识别与连续提取方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113763357B (zh) |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20020090121A1 (en) * | 2000-11-22 | 2002-07-11 | Schneider Alexander C. | Vessel segmentation with nodule detection |
CN103824309A (zh) * | 2014-03-12 | 2014-05-28 | 武汉大学 | 一种城市建成区边界自动提取方法 |
CN106651872A (zh) * | 2016-11-23 | 2017-05-10 | 北京理工大学 | 基于Prewitt算子的路面裂缝识别方法及*** |
CN111507971A (zh) * | 2020-04-20 | 2020-08-07 | 南京航空航天大学 | 一种隧道表面缺陷检测方法 |
CN112837290A (zh) * | 2021-02-03 | 2021-05-25 | 中南大学 | 一种基于种子填充算法的裂缝图像自动识别方法 |
-
2021
- 2021-09-08 CN CN202111048411.4A patent/CN113763357B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20020090121A1 (en) * | 2000-11-22 | 2002-07-11 | Schneider Alexander C. | Vessel segmentation with nodule detection |
CN103824309A (zh) * | 2014-03-12 | 2014-05-28 | 武汉大学 | 一种城市建成区边界自动提取方法 |
CN106651872A (zh) * | 2016-11-23 | 2017-05-10 | 北京理工大学 | 基于Prewitt算子的路面裂缝识别方法及*** |
CN111507971A (zh) * | 2020-04-20 | 2020-08-07 | 南京航空航天大学 | 一种隧道表面缺陷检测方法 |
CN112837290A (zh) * | 2021-02-03 | 2021-05-25 | 中南大学 | 一种基于种子填充算法的裂缝图像自动识别方法 |
Non-Patent Citations (6)
Title |
---|
LIANG LI 等: "Accurate identifcation and continuous extraction of fssures in loess areas based on unmanned aerial vehicle visible light images", 《ENVIRONMENTAL EARTH SCIENCES》, pages 1 - 19 * |
SAPTHAGIRIVASAN V 等: "Denoising and Fissure Extraction in High Resolution Isotropic CT Images Using Dual Tree Complex Wavelet Transform", 《2010 2ND INTERNATIONAL CONFERENCE ON SOFTWARE TECHNOLOGY AND ENGINEERING》, pages 1 - 362 * |
严世强 等: "基于渗流和区域生长联合分析的红外图像 裂缝病害检测方法", 《现代电子技术》, vol. 43, no. 18, pages 6 - 10 * |
吴志聪: "基于无人机影像的采动影响区植被特征变化精细化分析", 《中国优秀硕士学位论文全文数据库 基础科学辑》, no. 2, pages 006 - 2906 * |
张晶晶 等: "基于多尺度输入图像渗透模型的桥梁裂缝检测", 《计算机工程》, vol. 43, no. 2, pages 273 - 279 * |
李鹏 等: "基于K-means聚类的路面裂缝分割算法", 《计算机工程与设计》, vol. 41, no. 11, pages 3143 - 3147 * |
Also Published As
Publication number | Publication date |
---|---|
CN113763357B (zh) | 2023-11-28 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2020258899A1 (zh) | 一种基于高分遥感影像的山地景观建筑提取方法和设备 | |
WO2016172827A1 (zh) | 一种逐步求精的路面裂缝检测方法 | |
CN110765934B (zh) | 一种多源数据融合的地质灾害识别方法 | |
Awrangjeb et al. | Improved building detection using texture information | |
CN114387528A (zh) | 松材线虫病监测天空地一体化监测方法 | |
CN109584240A (zh) | 滑坡后缘裂缝位移图像识别方法 | |
CN107314957B (zh) | 一种岩石块度尺寸分布的测量方法 | |
CN108280812A (zh) | 一种基于图像增强的过火区域提取方法 | |
CN104463836A (zh) | 一种基于移动窗口的城市绿色空间遥感度量方法 | |
CN110889840A (zh) | 面向地物目标的高分6号遥感卫星数据的有效性检测方法 | |
CN102855627B (zh) | 基于光谱特性和拓扑关系的城市遥感影像阴影检测方法 | |
CN111274871B (zh) | 基于轻小型无人机的森林火灾林木受损程度提取方法 | |
CN110838117A (zh) | 一种基于孔壁图像的岩石面孔隙度识别方法 | |
CN114596495A (zh) | 一种基于Sentinel-2A遥感影像溜砂坡判识与自动提取方法 | |
CN108492288B (zh) | 基于随机森林的多尺度分层采样的高分卫星影像变化检测方法 | |
Zhan et al. | Quantitative analysis of shadow effects in high-resolution images of urban areas | |
CN110211128B (zh) | 基于遥感影像和dem的黄土高原梯田提取方法 | |
CN110796113B (zh) | 一种基于WorldView-2影像的城市蓝色地物检测方法 | |
CN106650663A (zh) | 建筑物真伪变化的判定方法及含此方法的伪变化去除方法 | |
CN111882573A (zh) | 一种基于高分辨率影像数据的耕地地块提取方法及*** | |
CN103971367A (zh) | 水文资料图像分割方法 | |
CN110889834A (zh) | 一种基于云计算的公路隧道围岩分级方法 | |
CN113705441A (zh) | 协同多光谱和sar影像的高时空分辨率地表水体提取方法 | |
CN107977968A (zh) | 基于建筑物阴影信息挖掘的建筑物分层检测方法 | |
CN113763357B (zh) | 基于可见光影像的矿区地裂缝精准识别与连续提取方法 |
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 | ||
CB03 | Change of inventor or designer information | ||
CB03 | Change of inventor or designer information |
Inventor after: Wu Zhicong Inventor after: Li Liang Inventor after: He Qian Inventor after: Yang Bin Inventor after: Yan Yong Inventor after: Yue Guangbo Inventor before: Li Liang Inventor before: Wu Zhicong Inventor before: He Qian Inventor before: Yang Bin Inventor before: Yan Yong Inventor before: Yue Guangbo |
|
GR01 | Patent grant | ||
GR01 | Patent grant |