CN110111361B - 一种基于多阈值自优化背景建模的运动目标检测方法 - Google Patents
一种基于多阈值自优化背景建模的运动目标检测方法 Download PDFInfo
- Publication number
- CN110111361B CN110111361B CN201910324690.9A CN201910324690A CN110111361B CN 110111361 B CN110111361 B CN 110111361B CN 201910324690 A CN201910324690 A CN 201910324690A CN 110111361 B CN110111361 B CN 110111361B
- Authority
- CN
- China
- Prior art keywords
- point
- pixel
- threshold
- value
- background
- 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.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 31
- 238000005457 optimization Methods 0.000 title claims abstract description 11
- 238000000034 method Methods 0.000 claims abstract description 31
- 238000001914 filtration Methods 0.000 claims abstract description 9
- 238000006243 chemical reaction Methods 0.000 claims description 12
- 238000005070 sampling Methods 0.000 claims description 11
- 230000003044 adaptive effect Effects 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000009977 dual effect Effects 0.000 claims description 2
- 230000006870 function Effects 0.000 claims description 2
- 238000012544 monitoring process Methods 0.000 abstract description 3
- 230000011218 segmentation Effects 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000002401 inhibitory effect Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Classifications
-
- 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
- G06T7/11—Region-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
- G06T7/136—Segmentation; Edge detection involving thresholding
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/215—Motion-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
-
- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- 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
- G06T2207/20032—Median filtering
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Image Analysis (AREA)
Abstract
Description
Claims (6)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910324690.9A CN110111361B (zh) | 2019-04-22 | 2019-04-22 | 一种基于多阈值自优化背景建模的运动目标检测方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910324690.9A CN110111361B (zh) | 2019-04-22 | 2019-04-22 | 一种基于多阈值自优化背景建模的运动目标检测方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN110111361A CN110111361A (zh) | 2019-08-09 |
CN110111361B true CN110111361B (zh) | 2021-05-18 |
Family
ID=67486119
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910324690.9A Active CN110111361B (zh) | 2019-04-22 | 2019-04-22 | 一种基于多阈值自优化背景建模的运动目标检测方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110111361B (zh) |
Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110807779A (zh) * | 2019-10-12 | 2020-02-18 | 湖北工业大学 | 一种基于区域分割的压缩计算鬼成像方法及系统 |
CN110930361B (zh) * | 2019-10-22 | 2022-03-25 | 西安理工大学 | 一种虚实物体遮挡检测方法 |
CN110910420B (zh) * | 2019-10-23 | 2022-05-20 | 同济大学 | 一种基于图像流的移动目标检测追踪方法 |
CN111047654A (zh) * | 2019-12-06 | 2020-04-21 | 衢州学院 | 一种基于色彩信息的高清高速视频背景建模方法 |
CN111008995B (zh) * | 2019-12-06 | 2023-07-18 | 衢州学院 | 面向高清高速视频的单通道多模态背景建模方法 |
CN113723364A (zh) * | 2021-09-28 | 2021-11-30 | 中国农业银行股份有限公司 | 运动目标识别方法及装置 |
CN113935962B (zh) * | 2021-09-29 | 2022-10-21 | 常州市新创智能科技有限公司 | 一种玻纤布的毛团检测方法 |
CN114567794B (zh) * | 2022-03-11 | 2023-06-30 | 浙江理工大学 | 一种直播视频背景替换方法 |
CN117278692B (zh) * | 2023-11-16 | 2024-02-13 | 邦盛医疗装备(天津)股份有限公司 | 一种医疗检测车病患监测数据脱敏保护方法 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102750712A (zh) * | 2012-06-07 | 2012-10-24 | 中山大学 | 一种基于局部时空流形学习的运动目标分割方法 |
CN106157332A (zh) * | 2016-07-07 | 2016-11-23 | 合肥工业大学 | 一种基于ViBe算法的运动检测优化方法 |
CN107564031A (zh) * | 2017-08-28 | 2018-01-09 | 西安文理学院 | 基于反馈背景提取的城市交通场景前景目标检测方法 |
CN108470354A (zh) * | 2018-03-23 | 2018-08-31 | 云南大学 | 视频目标跟踪方法、装置和实现装置 |
CN109660814A (zh) * | 2019-01-07 | 2019-04-19 | 福州大学 | 一种视频前景删除篡改的检测方法 |
Family Cites Families (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7260278B2 (en) * | 2003-11-18 | 2007-08-21 | Microsoft Corp. | System and method for real-time whiteboard capture and processing |
CN103729862A (zh) * | 2014-01-26 | 2014-04-16 | 重庆邮电大学 | 基于码本背景模型的自适应阈值运动目标检测方法 |
CN104392468B (zh) * | 2014-11-21 | 2017-08-04 | 南京理工大学 | 基于改进视觉背景提取的运动目标检测方法 |
US10373320B2 (en) * | 2017-03-17 | 2019-08-06 | Uurmi Systems PVT, LTD | Method for detecting moving objects in a video having non-stationary background |
CN107092890A (zh) * | 2017-04-24 | 2017-08-25 | 山东工商学院 | 基于红外视频的舰船检测及跟踪方法 |
CN109035296A (zh) * | 2018-06-28 | 2018-12-18 | 西安理工大学 | 一种改进的视频中运动物体检测方法 |
-
2019
- 2019-04-22 CN CN201910324690.9A patent/CN110111361B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102750712A (zh) * | 2012-06-07 | 2012-10-24 | 中山大学 | 一种基于局部时空流形学习的运动目标分割方法 |
CN106157332A (zh) * | 2016-07-07 | 2016-11-23 | 合肥工业大学 | 一种基于ViBe算法的运动检测优化方法 |
CN107564031A (zh) * | 2017-08-28 | 2018-01-09 | 西安文理学院 | 基于反馈背景提取的城市交通场景前景目标检测方法 |
CN108470354A (zh) * | 2018-03-23 | 2018-08-31 | 云南大学 | 视频目标跟踪方法、装置和实现装置 |
CN109660814A (zh) * | 2019-01-07 | 2019-04-19 | 福州大学 | 一种视频前景删除篡改的检测方法 |
Non-Patent Citations (3)
Title |
---|
Human Object Detection and Tracking using Background Subtraction for Sports Applications;R.Manikandan 等;《International Journal of Advanced Research in Computer and Communication Engineering》;20131031;第02卷(第10期);第4077-4080页 * |
基于视频图像的运动目标与阴影检测算法研究;王玮;《中国优秀硕士学位论文全文数据库 信息科技辑》;20181215(第(2018)12期);I138-1188 * |
融合时域信息的自适应ViBe算法;瞿中 等;《计算机工程与设计》;20190331;第40卷(第03期);第782-787页 * |
Also Published As
Publication number | Publication date |
---|---|
CN110111361A (zh) | 2019-08-09 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110111361B (zh) | 一种基于多阈值自优化背景建模的运动目标检测方法 | |
US8280165B2 (en) | System and method for segmenting foreground and background in a video | |
CN112036254B (zh) | 基于视频图像的运动车辆前景检测方法 | |
CN109993052B (zh) | 一种复杂场景下尺度自适应的目标跟踪方法和系统 | |
CN113111878B (zh) | 一种复杂背景下的红外弱小目标检测方法 | |
CN104952256A (zh) | 一种基于视频信息的交叉口处车辆的检测方法 | |
CN110555868A (zh) | 一种复杂地面背景下运动小目标检测方法 | |
CN111985314B (zh) | 一种基于ViBe与改进LBP的烟雾检测方法 | |
CN112927262B (zh) | 一种基于视频的相机镜头遮挡检测方法及系统 | |
CN110930327A (zh) | 基于级联深度残差网络的视频去噪方法 | |
CN110751635A (zh) | 一种基于帧间差分和hsv颜色空间的口腔检测方法 | |
CN112465842A (zh) | 基于U-net网络的多通道视网膜血管图像分割方法 | |
CN112949378A (zh) | 一种基于深度学习网络的细菌显微图像分割方法 | |
TW201032180A (en) | Method and device for keeping image background by multiple gauss models | |
CN110363197B (zh) | 基于改进视觉背景提取模型的视频感兴趣区域提取方法 | |
CN111583357A (zh) | 一种基于matlab系统的物体运动图像捕捉合成方法 | |
CN111667498B (zh) | 一种面向光学卫星视频的运动舰船目标自动检测方法 | |
CN104268845A (zh) | 极值温差短波红外图像的自适应双局部增强方法 | |
CN108010050B (zh) | 一种基于自适应背景更新和选择性背景更新的前景检测方法 | |
CN110880183A (zh) | 一种图像分割方法、设备和计算机可存储介质 | |
Zhang et al. | Dehazing with improved heterogeneous atmosphere light estimation and a nonlinear color attenuation prior model | |
CN107704864B (zh) | 基于图像对象性语义检测的显著目标检测方法 | |
CN104077786A (zh) | 一种基于自适应核密度估计模型的运动目标检测方法 | |
CN108257157B (zh) | 一种基于Lab色彩空间和ViBe改进的运动目标检测方法 | |
CN107766838B (zh) | 一种视频场景切换检测方法 |
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 |
Inventor after: Zhang Zipeng Inventor after: Liu Yifan Inventor after: Zou Qixiao Inventor after: Lan Tianze Inventor after: Zhou Bowen Inventor after: Wang Shuqing Inventor after: Ma Ye Inventor after: Cai Yingjing Inventor after: Wang Shen Inventor after: Qing Yihui Inventor after: Wang Chenxi Inventor before: Zhang Zipeng Inventor before: Liu Yifan Inventor before: Zou Qixiao Inventor before: Zhou Bowen Inventor before: Wang Shuqing Inventor before: Ma Ye Inventor before: Cai Yingjing Inventor before: Wang Shen Inventor before: Qing Yihui Inventor before: Wang Chenxi Inventor before: Lan Tianze |
|
CB03 | Change of inventor or designer information | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right |
Effective date of registration: 20210916 Address after: 430205 Hubei 1 East Lake New Technology Development Zone, Wuhan East 1 Industrial Park, No. 1, 25 high tech four road. Patentee after: WUHAN FENJIN INTELLIGENT MACHINE Co.,Ltd. Address before: 430068 1, Lijia 1 village, Nanhu, Wuchang District, Wuhan, Hubei Patentee before: HUBEI University OF TECHNOLOGY |
|
TR01 | Transfer of patent right | ||
PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A Moving Object Detection Method Based on Multi threshold Self optimizing Background Modeling Effective date of registration: 20230907 Granted publication date: 20210518 Pledgee: Industrial Bank Limited by Share Ltd. Wuhan branch Pledgor: WUHAN FENJIN INTELLIGENT MACHINE Co.,Ltd. Registration number: Y2023980055705 |
|
PE01 | Entry into force of the registration of the contract for pledge of patent right |