CN114820644A - 对图像的像素进行分类的方法和设备 - Google Patents
对图像的像素进行分类的方法和设备 Download PDFInfo
- Publication number
- CN114820644A CN114820644A CN202210101395.9A CN202210101395A CN114820644A CN 114820644 A CN114820644 A CN 114820644A CN 202210101395 A CN202210101395 A CN 202210101395A CN 114820644 A CN114820644 A CN 114820644A
- Authority
- CN
- China
- Prior art keywords
- edge detection
- detection algorithm
- pixels
- image
- ground truth
- 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
- 238000000034 method Methods 0.000 title claims abstract description 61
- 230000011218 segmentation Effects 0.000 claims abstract description 81
- 238000003708 edge detection Methods 0.000 claims abstract description 72
- 238000013528 artificial neural network Methods 0.000 claims abstract description 34
- 238000012545 processing Methods 0.000 claims description 17
- 238000012549 training Methods 0.000 claims description 14
- 239000011159 matrix material Substances 0.000 claims description 13
- 230000006870 function Effects 0.000 description 54
- 238000013527 convolutional neural network Methods 0.000 description 17
- 230000000875 corresponding effect Effects 0.000 description 12
- 239000003550 marker Substances 0.000 description 4
- 239000003086 colorant Substances 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 238000013500 data storage Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000295 complement effect Effects 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000000945 filler Substances 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 230000003278 mimic effect Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
- 238000010200 validation analysis Methods 0.000 description 1
- 239000013598 vector Substances 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 210000000857 visual cortex Anatomy 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
-
- 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
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/70—Labelling scene content, e.g. deriving syntactic or semantic representations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
-
- 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
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
- G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
- G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
- G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
- G06V10/7747—Organisation of the process, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- 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
- G06T2207/10004—Still image; Photographic 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
- G06T2207/20021—Dividing image into blocks, subimages or windows
-
- 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
- G06T2207/20081—Training; Learning
-
- 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
- G06T2207/20084—Artificial neural networks [ANN]
-
- 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
- G06T2207/30248—Vehicle exterior or interior
- G06T2207/30252—Vehicle exterior; Vicinity of vehicle
- G06T2207/30261—Obstacle
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Software Systems (AREA)
- Computing Systems (AREA)
- Data Mining & Analysis (AREA)
- Medical Informatics (AREA)
- Databases & Information Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- Computational Linguistics (AREA)
- Geometry (AREA)
- Biodiversity & Conservation Biology (AREA)
- Biomedical Technology (AREA)
- Molecular Biology (AREA)
- Image Analysis (AREA)
Abstract
Description
Claims (15)
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP21154378.0A EP4036792A1 (en) | 2021-01-29 | 2021-01-29 | Method and device for classifying pixels of an image |
EP21154378.0 | 2021-01-29 |
Publications (1)
Publication Number | Publication Date |
---|---|
CN114820644A true CN114820644A (zh) | 2022-07-29 |
Family
ID=74418332
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210101395.9A Pending CN114820644A (zh) | 2021-01-29 | 2022-01-27 | 对图像的像素进行分类的方法和设备 |
Country Status (3)
Country | Link |
---|---|
US (1) | US20220245955A1 (zh) |
EP (1) | EP4036792A1 (zh) |
CN (1) | CN114820644A (zh) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116052061A (zh) * | 2023-02-21 | 2023-05-02 | 嘉洋智慧安全科技(北京)股份有限公司 | 事件监测方法、装置、电子设备及存储介质 |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US12002217B1 (en) * | 2021-10-25 | 2024-06-04 | Zoox, Inc. | Detection box determination based on pixel clustering |
IL297653B2 (en) * | 2022-10-25 | 2024-03-01 | Geox Gis Innovations Ltd | A system and method for segment-aware semantic segmentation |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104346620B (zh) * | 2013-07-25 | 2017-12-29 | 佳能株式会社 | 对输入图像中的像素分类的方法和装置及图像处理*** |
US10635927B2 (en) * | 2017-03-06 | 2020-04-28 | Honda Motor Co., Ltd. | Systems for performing semantic segmentation and methods thereof |
CN112070779B (zh) * | 2020-08-04 | 2022-03-15 | 武汉大学 | 一种基于卷积神经网络弱监督学习的遥感影像道路分割方法 |
-
2021
- 2021-01-29 EP EP21154378.0A patent/EP4036792A1/en active Pending
-
2022
- 2022-01-19 US US17/579,536 patent/US20220245955A1/en active Pending
- 2022-01-27 CN CN202210101395.9A patent/CN114820644A/zh active Pending
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116052061A (zh) * | 2023-02-21 | 2023-05-02 | 嘉洋智慧安全科技(北京)股份有限公司 | 事件监测方法、装置、电子设备及存储介质 |
CN116052061B (zh) * | 2023-02-21 | 2024-02-27 | 嘉洋智慧安全科技(北京)股份有限公司 | 事件监测方法、装置、电子设备及存储介质 |
Also Published As
Publication number | Publication date |
---|---|
EP4036792A1 (en) | 2022-08-03 |
US20220245955A1 (en) | 2022-08-04 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109978893B (zh) | 图像语义分割网络的训练方法、装置、设备及存储介质 | |
CN111160379B (zh) | 图像检测模型的训练方法及装置、目标检测方法及装置 | |
CN109478239B (zh) | 检测图像中的对象的方法和对象检测*** | |
CN109815997B (zh) | 基于深度学习的识别车辆损伤的方法和相关装置 | |
US20190019042A1 (en) | Computer implemented detecting method, computer implemented learning method, detecting apparatus, learning apparatus, detecting system, and recording medium | |
CN114820644A (zh) | 对图像的像素进行分类的方法和设备 | |
CN102693432B (zh) | 使用可靠局部模型更新来调节畅通路径检测 | |
CN109086668B (zh) | 基于多尺度生成对抗网络的无人机遥感影像道路信息提取方法 | |
JP5815910B2 (ja) | マルチキュー・オブジェクトの検出および分析のための方法、システム、製品、およびコンピュータ・プログラム(マルチキュー・オブジェクトの検出および分析) | |
CN111767878B (zh) | 嵌入式设备中基于深度学习的交通标志检测方法及*** | |
CN102682301B (zh) | 使用附加分类器来调节畅通路径检测 | |
CN110781980B (zh) | 目标检测模型的训练方法、目标检测方法及装置 | |
US10824881B2 (en) | Device and method for object recognition of an input image for a vehicle | |
KR20200096114A (ko) | 자율 주행 네트워크의 검출 프로세스를 검증하는 설명 가능한 인공지능을 사용하여 운전자에게 잠재적 위험 상황에 대해 경고함으로써 기능적 안전성을 제공하는 학습 방법 및 학습 장치, 그리고 이를 이용한 테스팅 방법 및 테스팅 장치 | |
JP2021528757A (ja) | 機械学習モデルの出力から推論されるインスタンスセグメンテーション | |
US11908178B2 (en) | Verification of computer vision models | |
CN112241757A (zh) | 用于操作神经网络的设备和方法 | |
CN115100614A (zh) | 车辆感知***的评估方法、装置、车辆及存储介质 | |
Saravanarajan et al. | Improving semantic segmentation under hazy weather for autonomous vehicles using explainable artificial intelligence and adaptive dehazing approach | |
CN113903041A (zh) | 文本识别方法、装置、车辆及存储介质 | |
CN112241758A (zh) | 用于评估显著性图确定器的设备和方法 | |
CN111401359A (zh) | 目标识别方法、装置、电子设备和存储介质 | |
CN111860261B (zh) | 一种客流值的统计方法、装置、设备及介质 | |
CN114360291A (zh) | 驾驶员危险预警方法、装置、设备及存储介质 | |
KR20190093752A (ko) | 딥 러닝을 이용한 씬 텍스트 검출 방법 및 시스템 |
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 | ||
TA01 | Transfer of patent application right | ||
TA01 | Transfer of patent application right |
Effective date of registration: 20240308 Address after: Luxembourg Applicant after: Aptiv Manufacturing Management Services Co. Country or region after: Luxembourg Address before: Babado J San Michael Applicant before: Aptiv Technologies Ltd. Country or region before: Barbados |
|
TA01 | Transfer of patent application right | ||
TA01 | Transfer of patent application right |
Effective date of registration: 20240320 Address after: Schaffhausen Applicant after: APTIV Technology Co.,Ltd. Country or region after: Switzerland Address before: Luxembourg Applicant before: Aptiv Manufacturing Management Services Co. Country or region before: Luxembourg |