查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

113-2 342181 影像及訊號辨識 1 3.0 3 ★ 陳紅章機電所
半導體學位學程
機電博所
機電外國學生專班 13 0 機電所.半導體班.機電博含外生專班合開,限30人

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
113-2	342181	影像及訊號辨識	1	3.0	3	★	陳紅章	機電所半導體學位學程機電博所機電外國學生專班	13	0	機電所.半導體班.機電博含外生專班合開,限30人

教學大綱與進度：

教師姓名陳紅章　教師諮商時間(Office Hours)

Email hctran@ntut.edu.tw

最後更新時間 2024-12-21 23:03:21

課程大綱本課程介紹主題包括基本的影像處理算法，如直方圖均衡化；影像濾波與卷積；輪廓提取、霍夫變換，以及模式辨識與分類。 This course introduce basic image processing algorithm such as histogram equalization; Image Filtering and Convolution; Contour Extractions, Hough Transform , Pattern Recognition and Classification

課程進度 Weeks 1-2: Introduction to Image and Signal Processing Overview of image and signal processing Basics of digital image representation Introduction to MATLAB or Python for image and signal processing Weeks 3-4: Image Enhancement Techniques Histogram equalization Spatial domain methods (smoothing, sharpening) Frequency domain methods (Fourier transform) Weeks 5-6: Image Filtering and Convolution Convolution operation Linear and nonlinear filtering Edge detection techniques Weeks 7-8: Image Transformations Image rotation, scaling, and translation Geometric transformations Introduction to wavelet transforms Weeks 9-10: Image Segmentation Thresholding methods Region-based segmentation Clustering algorithms for segmentation Weeks 11-12: Image Feature Extraction Feature extraction techniques Corner detection and Harris corner detector SIFT and SURF feature descriptors Weeks 13-14: Introduction to Signal Recognition Overview of signal recognition Signal processing techniques Feature extraction from signals Weeks 15-16: Pattern Recognition and Classification Introduction to pattern recognition Supervised and unsupervised learning Classification algorithms (e.g., SVM, k-NN) Weeks 17-18: Final Project and Review Application of image and signal recognition techniques in a final project Review of key concepts Preparation for final assessments

評量方式與標準 Homework 30% Midterm 30% Final Projects 40%

使用教材、參考書目或其他 【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】

使用外文原文書：是
"Image Processing, Analysis, and Machine Vision" by Milan Sonka, Vaclav Hlavac, and Roger Boyle

課程諮詢管道 If students would like to consult about the course, please contact me via mail email address: hctran@ntut.edu.tw

延伸教學與資源

課程對應SDGs指標 SDG4：優質教育（Quality Education）
SDG5：性別平等（Gender Equality）
SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth）
SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）
SDG17：夥伴關係（Partnerships for the Goals）

課程是否導入AI

備註

教師姓名	陳紅章　教師諮商時間(Office Hours)
Email	hctran@ntut.edu.tw
最後更新時間	2024-12-21 23:03:21
課程大綱	本課程介紹主題包括基本的影像處理算法，如直方圖均衡化；影像濾波與卷積；輪廓提取、霍夫變換，以及模式辨識與分類。 This course introduce basic image processing algorithm such as histogram equalization; Image Filtering and Convolution; Contour Extractions, Hough Transform , Pattern Recognition and Classification
課程進度	Weeks 1-2: Introduction to Image and Signal Processing Overview of image and signal processing Basics of digital image representation Introduction to MATLAB or Python for image and signal processing Weeks 3-4: Image Enhancement Techniques Histogram equalization Spatial domain methods (smoothing, sharpening) Frequency domain methods (Fourier transform) Weeks 5-6: Image Filtering and Convolution Convolution operation Linear and nonlinear filtering Edge detection techniques Weeks 7-8: Image Transformations Image rotation, scaling, and translation Geometric transformations Introduction to wavelet transforms Weeks 9-10: Image Segmentation Thresholding methods Region-based segmentation Clustering algorithms for segmentation Weeks 11-12: Image Feature Extraction Feature extraction techniques Corner detection and Harris corner detector SIFT and SURF feature descriptors Weeks 13-14: Introduction to Signal Recognition Overview of signal recognition Signal processing techniques Feature extraction from signals Weeks 15-16: Pattern Recognition and Classification Introduction to pattern recognition Supervised and unsupervised learning Classification algorithms (e.g., SVM, k-NN) Weeks 17-18: Final Project and Review Application of image and signal recognition techniques in a final project Review of key concepts Preparation for final assessments
評量方式與標準	Homework 30% Midterm 30% Final Projects 40%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】使用外文原文書：是 "Image Processing, Analysis, and Machine Vision" by Milan Sonka, Vaclav Hlavac, and Roger Boyle
課程諮詢管道	If students would like to consult about the course, please contact me via mail email address: hctran@ntut.edu.tw
延伸教學與資源
課程對應SDGs指標	SDG4：優質教育（Quality Education） SDG5：性別平等（Gender Equality） SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure） SDG17：夥伴關係（Partnerships for the Goals）
課程是否導入AI
備註