Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Fall Semester
Year 2025 350088 Digital Image Processing 1 3.0 3 ★ CHIN-SHENG CHEN GAT
MSAI
半導體學位學程 2 0 自動化所和創新AI、半導體合開

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2025	350088	Digital Image Processing	1	3.0	3	★	CHIN-SHENG CHEN	GAT MSAI 半導體學位學程	2	0	自動化所和創新AI、半導體合開

Course Plan：

Instructor CHIN-SHENG CHEN　Office Hours

Email saint@ntut.edu.tw

Last Updated 2025-05-30 16:31:46

Course Objective 本課程在使學生瞭解數位影像之觀念及相關技術，並學習實際用高階語言實現數位影像處理之技術。內容包含：(1)介紹，(2)數位影像基礎，(3)強度轉換與空間域濾波，(4)頻域濾波，(5)形態學影像處理，(6)影像分割，(7)影像表示與描述，(8)彩色影像處理，(9)業界講師應用例演講。 This course is a graduate-level introductory course to digital image processing. The goal of this course is to let students to understand the concepts and techniques used in the field of digital image processing. In addition, students will be using the high level language (C, C++) to complete the programming of the corresponding techniques. The contents: (1) Introduction, (2) Digital Image Fundamentals, (3) Intensity Transformations and Spatial Filtering, (4) Filtering in the Frequency Domain, (5) Morphological Image Processing, (6) Image Segmentation, (7) Representation and Description, (8) Color Image Processing, (9) Specific topic by industrial teacher.

Course Schedule Week 01 : Administrative/ Course introduction Week 02 : Chap 1. Introduction Week 03 : Chap 2. Digital Image Fundamentals Week 04 : Chap 2. Digital Image Fundamentals Chap 3. Intensity Transformations and Spatial Filtering Week 05 : Chap 3. Intensity Transformations and Spatial Filtering Week 06 : Chap 4. Filtering in the Frequency Domain Week 07 : Chap 4. Filtering in the Frequency Domain Week 08 : Chap 9. Morphological Image Processing Week 09 : Midterm Week 10 : Chap 9. Morphological Image Processing Week 11 : Chap 10. Image Segmentation Week 12 : Chap 10. Image Segmentation Week 13 : Chap 11. Representation and Description Week 14 : Chap 6. Color Image Processing/ Term project discussion Week 15 : Specific topic by industrial teacher Week 16 : Term project presentation(1/2) Week 17 : 2026 New year Week 18 : Term project presentation(2/2)

Evaluation and grading policy Homework assignment (4): 50% Midterm: 20% Term project and competition: 30%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Textbook R. C. Gonzalez and R. E. Woods, “Digital Image Processing,” 3th edition, Prentice Hall, 2010. Reference book 1.R. C. Gonzalez, R. E. Woods and S. L. Eddins, “Digital Image Processing Using MATLAB,” McGraw-Hill, 2011. 2.S. E. Umbaugh, Digital Image Processing and Analysis, 2nd edition, CPC Press, 2011.

The access to curricular consultation 1. The student can access curricular consultation by the instructor's email address.

The course corresponds to the SDGs SDG4：優質教育（Quality Education）
SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）

Does the course incorporate AI AI2：鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）

Note
The course lecture will be offered online via Google meet if required.

Instructor	CHIN-SHENG CHEN　Office Hours
Email	saint@ntut.edu.tw
Last Updated	2025-05-30 16:31:46
Course Objective	本課程在使學生瞭解數位影像之觀念及相關技術，並學習實際用高階語言實現數位影像處理之技術。內容包含：(1)介紹，(2)數位影像基礎，(3)強度轉換與空間域濾波，(4)頻域濾波，(5)形態學影像處理，(6)影像分割，(7)影像表示與描述，(8)彩色影像處理，(9)業界講師應用例演講。 This course is a graduate-level introductory course to digital image processing. The goal of this course is to let students to understand the concepts and techniques used in the field of digital image processing. In addition, students will be using the high level language (C, C++) to complete the programming of the corresponding techniques. The contents: (1) Introduction, (2) Digital Image Fundamentals, (3) Intensity Transformations and Spatial Filtering, (4) Filtering in the Frequency Domain, (5) Morphological Image Processing, (6) Image Segmentation, (7) Representation and Description, (8) Color Image Processing, (9) Specific topic by industrial teacher.
Course Schedule	Week 01 : Administrative/ Course introduction Week 02 : Chap 1. Introduction Week 03 : Chap 2. Digital Image Fundamentals Week 04 : Chap 2. Digital Image Fundamentals Chap 3. Intensity Transformations and Spatial Filtering Week 05 : Chap 3. Intensity Transformations and Spatial Filtering Week 06 : Chap 4. Filtering in the Frequency Domain Week 07 : Chap 4. Filtering in the Frequency Domain Week 08 : Chap 9. Morphological Image Processing Week 09 : Midterm Week 10 : Chap 9. Morphological Image Processing Week 11 : Chap 10. Image Segmentation Week 12 : Chap 10. Image Segmentation Week 13 : Chap 11. Representation and Description Week 14 : Chap 6. Color Image Processing/ Term project discussion Week 15 : Specific topic by industrial teacher Week 16 : Term project presentation(1/2) Week 17 : 2026 New year Week 18 : Term project presentation(2/2)
Evaluation and grading policy	Homework assignment (4): 50% Midterm: 20% Term project and competition: 30%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Textbook R. C. Gonzalez and R. E. Woods, “Digital Image Processing,” 3th edition, Prentice Hall, 2010. Reference book 1.R. C. Gonzalez, R. E. Woods and S. L. Eddins, “Digital Image Processing Using MATLAB,” McGraw-Hill, 2011. 2.S. E. Umbaugh, Digital Image Processing and Analysis, 2nd edition, CPC Press, 2011.
The access to curricular consultation	1. The student can access curricular consultation by the instructor's email address.
The course corresponds to the SDGs	SDG4：優質教育（Quality Education） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）
Does the course incorporate AI	AI2：鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
Note	The course lecture will be offered online via Google meet if required.