CL2023001575A1 - Técnicas de aumento de imagen para inspección visual automatizada - Google Patents
Técnicas de aumento de imagen para inspección visual automatizadaInfo
- Publication number
- CL2023001575A1 CL2023001575A1 CL2023001575A CL2023001575A CL2023001575A1 CL 2023001575 A1 CL2023001575 A1 CL 2023001575A1 CL 2023001575 A CL2023001575 A CL 2023001575A CL 2023001575 A CL2023001575 A CL 2023001575A CL 2023001575 A1 CL2023001575 A1 CL 2023001575A1
- Authority
- CL
- Chile
- Prior art keywords
- images
- avi
- techniques
- image
- visual inspection
- Prior art date
Links
- 238000000034 method Methods 0.000 title abstract 4
- 238000011179 visual inspection Methods 0.000 title abstract 2
- 230000007547 defect Effects 0.000 abstract 2
- 238000013528 artificial neural network Methods 0.000 abstract 1
- 238000013135 deep learning Methods 0.000 abstract 1
- 238000003908 quality control method Methods 0.000 abstract 1
- 230000017105 transposition Effects 0.000 abstract 1
- 238000010200 validation analysis Methods 0.000 abstract 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/60—Editing figures and text; Combining figures or text
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
-
- 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
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/90—Investigating the presence of flaws or contamination in a container or its contents
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/60—Rotation of whole images or parts thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/40—Image enhancement or restoration using histogram techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/77—Retouching; Inpainting; Scratch removal
-
- 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
- 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
-
- 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
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Quality & Reliability (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Artificial Intelligence (AREA)
- Mathematical Physics (AREA)
- Biomedical Technology (AREA)
- Multimedia (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
- Eye Examination Apparatus (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
Diversas técnicas facilitan el desarrollo de una biblioteca de imágenes que puede usarse para entrenar y/o validar un modelo de inspección visual automatizada (AVI), una red neuronal de AVI de este tipo para la clasificación de imágenes. En un aspecto, se usa un algoritmo de transposición aritmética para generar imágenes sintéticas a partir de imágenes originales transponiendo características (por ejemplo, defectos) a las imágenes originales, con realismo a nivel de píxel. En otros aspectos, se usan técnicas de restauración de imagen digital para generar imágenes sintéticas realistas a partir de imágenes originales. Pueden usarse técnicas de restauración de imagen basadas en aprendizaje profundo para añadir, eliminar y/o modificar defectos u otras características representadas. En otros aspectos adicionales, se usan técnicas de control de calidad para evaluar la idoneidad de las bibliotecas de imágenes para el entrenamiento y/o validación de modelos de AVI, y/o para evaluar si las imágenes individuales son adecuadas para su inclusión en tales bibliotecas.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US202063120508P | 2020-12-02 | 2020-12-02 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CL2023001575A1 true CL2023001575A1 (es) | 2023-11-10 |
Family
ID=79025147
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CL2023001575A CL2023001575A1 (es) | 2020-12-02 | 2023-06-01 | Técnicas de aumento de imagen para inspección visual automatizada |
Country Status (13)
| Country | Link |
|---|---|
| US (1) | US20240095983A1 (es) |
| EP (1) | EP4256524A1 (es) |
| JP (1) | JP2023551696A (es) |
| KR (1) | KR20230116847A (es) |
| CN (1) | CN116830157A (es) |
| AR (1) | AR124217A1 (es) |
| AU (1) | AU2021392638A1 (es) |
| CA (1) | CA3203163A1 (es) |
| CL (1) | CL2023001575A1 (es) |
| IL (1) | IL303112A (es) |
| MX (1) | MX2023006357A (es) |
| TW (1) | TW202240546A (es) |
| WO (1) | WO2022119870A1 (es) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20230135102A (ko) * | 2021-02-18 | 2023-09-22 | 파라타 시스템즈, 엘엘씨 | 의약품 패키징 시스템의 특성에 기초하여 의약품 패키지콘텐츠를 검증하기 위한 방법, 시스템 및 컴퓨터 프로그램 제품 |
| WO2024035640A2 (en) * | 2022-08-12 | 2024-02-15 | Saudi Arabian Oil Company | Probability of detection of lifecycle phases of corrosion under insulation using artificial intelligence and temporal thermography |
-
2021
- 2021-12-01 WO PCT/US2021/061309 patent/WO2022119870A1/en active Application Filing
- 2021-12-01 TW TW110144774A patent/TW202240546A/zh unknown
- 2021-12-01 IL IL303112A patent/IL303112A/en unknown
- 2021-12-01 CA CA3203163A patent/CA3203163A1/en active Pending
- 2021-12-01 US US18/039,898 patent/US20240095983A1/en active Pending
- 2021-12-01 EP EP21831181.9A patent/EP4256524A1/en active Pending
- 2021-12-01 JP JP2023532732A patent/JP2023551696A/ja active Pending
- 2021-12-01 KR KR1020237021712A patent/KR20230116847A/ko unknown
- 2021-12-01 AU AU2021392638A patent/AU2021392638A1/en active Pending
- 2021-12-01 MX MX2023006357A patent/MX2023006357A/es unknown
- 2021-12-01 CN CN202180092354.1A patent/CN116830157A/zh active Pending
- 2021-12-01 AR ARP210103331A patent/AR124217A1/es unknown
-
2023
- 2023-06-01 CL CL2023001575A patent/CL2023001575A1/es unknown
Also Published As
| Publication number | Publication date |
|---|---|
| EP4256524A1 (en) | 2023-10-11 |
| WO2022119870A1 (en) | 2022-06-09 |
| IL303112A (en) | 2023-07-01 |
| JP2023551696A (ja) | 2023-12-12 |
| TW202240546A (zh) | 2022-10-16 |
| CA3203163A1 (en) | 2022-06-09 |
| US20240095983A1 (en) | 2024-03-21 |
| CN116830157A (zh) | 2023-09-29 |
| MX2023006357A (es) | 2023-06-13 |
| AU2021392638A1 (en) | 2023-06-22 |
| KR20230116847A (ko) | 2023-08-04 |
| AR124217A1 (es) | 2023-03-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CL2023001575A1 (es) | Técnicas de aumento de imagen para inspección visual automatizada | |
| McCormack et al. | Ten questions concerning generative computer art | |
| CL2022003058A1 (es) | Plataformas de aprendizaje profundo para la inspección visual automatizada | |
| Amutha | Impact of e-content integration in science on the learning of students at tertiary level | |
| Hiranyachattada et al. | Using Mobile Augmented Reality to Enhancing Students' Conceptual Understanding of Physically-Based Rendering in 3D Animation. | |
| Veermans et al. | Pedagogy in educational simulations and games | |
| Yakob et al. | The effectiveness of science experiment through multimedia teaching materials to improve students’ critical thinking | |
| Vasilakis et al. | Remote teaching advanced rendering topics using the rayground platform | |
| Kim et al. | The history of base-ten-blocks: Why and who made base-ten-blocks | |
| Wu | Designing a digital multimedia interactive book for industrial metrology measurement learning | |
| Mukasheva et al. | Visualization of sorting algorithms in the virtual reality environment | |
| Adeniyi et al. | Reshaping education and entrepreneurial skills for Industry 4.0 | |
| Kim et al. | Exploring AI-based Teaching and Learning Activities for Software Education in Kindergarteners to the Second Graders | |
| Szymczyk | Presentation of the most interesting geographical places using virtual reality technology | |
| Saari et al. | Computational thinking–Essential and pervasive toolset | |
| Srisawasdi et al. | Effect of simulation-based inquiry with dual-situated learning model on change of student’s conception | |
| Rahmadani et al. | Improving students’ conceptual knowledge on optical device materials with computer simulations | |
| Ubaidullah et al. | Development of a new application for multimedia learning with animation exaggeration based on ADDIE model | |
| van Langeveld et al. | Digital visualization tools improve teaching 3d character modeling | |
| Grgurina et al. | Investigating informatics teachers’ initial pedagogical content knowledge on modeling and simulation | |
| Nosirova et al. | USING AUTHENTIC MATERIALS IN ESP CLASSROOMS | |
| Psomos et al. | A supporting framework for the creation of digital stories and learning programming by the students within Kodu, Scratch and Storytelling Alice | |
| Nurhajati | Mobile learning media development on kampung kb management training material for family planning field worker in East Java | |
| NNEJI | EFFECT OF AUDIO ANIMATION INSTRUCTIONAL MEDIA ON MIDDLE BASIC EDUCATION PUPILS’ACHIEVEMENT, AND INTEREST IN ENGLISH LANGUAGE IN AGBANI EDUCATION ZONE | |
| Moser et al. | Toward a Smart Pedagogy: Devising a Methodology for Innovation |