授課教授: 傅楸善教授
email: fuh@csie.ntu.edu.tw web: http://www.csie.ntu.edu.tw/~fuh Tel: (02)23625336 轉 327
辦公室時間: 週二上午 11:00AM~11:59AM
課程資訊
上課時間:
週二下午 789 節
(2:20PM ~ 5:20PM)
上課地點: 資訊工程系 德田館 R103
助教:李詠億
phone: 0975032973
email: charlie8803290@gmail.com
office hour:週二上午11:30AM~1:30PM, R328
或請來信預約
助教:邱議禾
phone: 0968526873
email: r11922189@csie.ntu.edu.tw
office hour:週二上午11:30AM~1:30PM, R328
或請來信預約
Textbook
[1] R. M. Haralick and L. G. Shapiro, Computer and Robot Vision, Vol. I, Addison Wesley, Reading, MA, 1992.
References
[1] R. Jain, R. Kasturi, and B. G. Schunck, Machine Vision, McGraw-Hill, New York, 1995. [2] C. Gonzalez and R. E. Woods, Digital Image Processing, Addison Wesley, Reading, MA, 1992. [3] R. Szeliski, Computer Vision: Algorithms and Applications, Springer-Verlag, London, 2011.
Grading
Class Materials
Textbook
- Here pwd: 2010cv1
Handouts (PDF Format). (Past Materials)
- Introduction and Chapter 1: Computer Vision Overview
- Chapter 2: Binary Machine Vision - Thresholding and Segmentation
- Chapter 3: Binary Machine Vision - Region Analysis
- Chapter 4: Statistical Pattern Recognition
- Chapter 5: Mathematical Morphology
- Chapter 6: Neighborhood Operator
- Chapter 7: Conditioning and Labeling
- Chapter 8: The Facet Model
- Chapter 9: Texture
- Chapter 10: Image Segmentation
- Chapter 11: Arc Extraction and Segmentation
- Computer Vision 1 - Typo and Errata
Handouts (PPT Format)
- Introduction and Chapter 1: Computer Vision Overview (2023/09/06 Updated)
- Chapter 2: Binary Machine Vision - Thresholding and Segmentation | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023
- Chapter 3: Binary Machine Vision - Region Analysis | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023
- Chapter 4: Statistical Pattern Recognition | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023
- Chapter 5: Mathematical Morphology | 2012 | 2013 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023
- Chapter 6: Neighborhood Operator | 2012 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023
- Chapter 7: Conditioning and Labeling | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 (pdf) | 2020 | 2021 | 2022 | 2023
- Chapter 8: The Facet Model | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 (pdf_v2) | 2020 | 2021 | 2022 | 2023
- Chapter 9: Texture | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 (pdf_v2) | 2020 | 2021 | 2022 | 2023
- Chapter 10: Image Segmentation | 2013 | 2015 | 2016 | 2017 | 2018 | 2019 (pdf) | 2020 | 2021 | 2022 | 2023
- Chapter 11: Arc Extraction and Segmentation | 2013 | 2017 | 2018 | 2019 (pdf) | 2020 | 2021 | 2022 | 2023
Research
- 9/12 Super-Resolution
- 9/19 Vehicle_License_Plate_Image_Restoration
- 9/26 Toric_IOL_Implant_Digital_Alignment
- 10/03 Water Valve Defect Inspection
- 10/17 Hand gesture recognition
- 10/31 AIoT Development Platform for Active Speaker Detection
- 11/07 FCN_ECG_REMOVAL
- 11/14 Research_LinFusion
- 11/28 Speech Enhancement in Edge Devices
- 12/05 Reducing obstructive sleep apnea after OGS surgery by evaluating the cephalometric parameters
Homework Regulations
- Homeworks are to be turned in ON TIME by FTP FileZilla Client ( IP: 140.112.31.83, account: 2023cv1, password: 2023cv1, port: 12000) (before class starts)! Late homeworks will be subjected to grade penalties! Please compress the homework files to a zip file. The filename format is [STUDENT-ID]_HW[HW-NUMBER]_ver[VERSION-NUMBER].zip (e.g. R07922666_HW1_ver1.zip).
- HomeWork File Format and content:
- Compressed File
- |
- |-------- Report [.pdf]
- |------- Source Code [.py, .cpp ....]
- Only electronic submissions are allowed! The homework should include two parts, the report and the source code. Report formats are restricted to Adobe PDF format. Failure to fulfill the file formats when submitting your homework will result with no grades. Also, please take note of the fields for submission.
- Your homework report should include the following contents: a brief discription of your homework, the algorithm you used, your parameters (if any), your principal code fragment, and the resulting images (please paste the images in your report file).
- Do not copy homeworks from others. Copying is cheating, and cheating is shameful. You and the person who let you copy his/her homework will both get a 0. In addition, you could be subjected to an on site demostration for the following assignments.
- Any programming language are allowed to used for homework. Do not use any library except basic I/O function (e.g. read file, write file, show image).
Homeworks
Reference Materials
- Benchmark Image
-
Windows bitmap vision format lena.bmp
- OpenCV C++ homework template for Visual Studio 2015
-
If you want to use OpenCV C++ to do your homework, you can download the template here !
Do not submit the whole project, but only the source code.
In addition, we will set the maximum file size to 100MB on our FTP server.
- About lossy compression modes.
-
Lossy compression modes such as the JPG format will not be equal to the original lena.bmp image when restored. Information loss is inevitable when using such image compression modes. Please avoid using such modes at all cost or your final resulting image will differ from the correct solution.