| Academic Year |
2024Year |
School/Graduate School |
School of Informatics and Data Science |
| Lecture Code |
KA206001 |
Subject Classification |
Specialized Education |
| Subject Name |
画像処理 |
Subject Name
（Katakana） |
ガゾウショリ |
Subject Name in
English |
Image Processing |
| Instructor |
HIGAKI TORU |
Instructor
(Katakana) |
ヒガキ トオル |
| Campus |
Higashi-Hiroshima |
Semester/Term |
3rd-Year, First Semester, 2Term |
| Days, Periods, and Classrooms |
(2T) Thur5-8：ENG 219 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| Lecture and programming exercises |
| Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
B
:
Japanese／English |
| Course Level |
3
:
Undergraduate High-Intermediate
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
02
:
Information Science |
| Eligible Students |
3rd Year |
| Keywords |
image processing, image recognition, computer graphics |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | 電気・電子・システム・情報系プログラム
（能力・技能）
・電気，電子，システム，情報工学分野の基礎概念，知識および手法を具体的・専門的な問題に応用する能力。 |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | Computer Science Program
（Abilities and Skills）
・D3. Knowledge of hardware and software and programming ability to process data efficiently.
Data Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
Intelligence Science Program
（Abilities and Skills）
・D2. Information processing ability and data analysis ability to contribute to the application and development of artificial intelligence and IoT. |
|---|
Class Objectives
/Class Outline |
The goal of this lecture is to deliver basic knowledge and algorithms of image processing and recognition, and computer graphics. |
| Class Schedule |
lesson1
imaging process
color model and intensity transformation
lesson2
filtering
restoration
lesson3
geometric transformation
lesson4
binary image processing
lesson5
region process
lesson6
feature extraction
lesson7
pattern matching
lesson8
pattern recognition
lesson9
movie processing
lesson10
structure from motion
photometric analysis
lesson11
camera model, coordinate transformation, viewing pipeline
lesson12
modeling
lesson13
rendering, hidden surface removal
lesson14
shading, texture mapping
lesson15
animation
programing projects are assigned.
intermediate exams will be planned. |
Text/Reference
Books,etc. |
教科書
ディジタル画像処理 [改訂新版]，画像情報教育振興協会, ISBN978-4-903474-50-2 (2015/3/9)
参考書
ビジュアル情報処理 -CG・画像処理入門- [改訂新版], 画像情報教育振興協会 (2017/3)
コンピュータグラフィックス[改訂新版], 画像情報教育振興協会, ISBN978-4-903474-49-6 (2015/3/9) |
PC or AV used in
Class,etc. |
|
| (More Details) |
Books, PDF handouts, PC |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
refer chapters of the textbooks |
| Requirements |
Prepare a laptop PC for projects and referencing PDF handouts during lectures. |
| Grading Method |
exams and project reports are evaluated. |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |