智慧光電影像處理實作

Implementation of Intelligent Photonic Image Processing

學期

114-2

學分

1 學分

當期課號

638604

永久課號

PTIB30014

開課單位

影像與生醫光電研究所

授課教師

陳顯禎

校區

歸仁

類別

選修

上課時間表

節	週四
6 14:20–15:10	智慧光電影像處理實作 CM214

* 根據陽明交大上課時間表所列

概述

選修 1 學分每週時數：講演：1小時課程目的：智慧光電影像處理實作﹙Implementation of Intelligent Photonic Image Processing﹚以於空間域光電影像處理為主軸，搭配深度學習於影像辨識，先藉由連續與離散傅立葉轉換﹙Fourier transform﹚來做光電影像分析以及在光電訊號系統上應用，並著重理論與實作的搭配，使修課的學生能真正的了解連續與離散的光電影像處理之原理與系統。利用這些原理基礎來實作單元一﹙二維連續空間﹚：光學特徵辨識系統﹙Lab 1﹚；單元二﹙二維離散空間﹚：適應性濾波器之影像強化技術﹙Lab 2﹚；單元三﹙影像智慧辨識﹚：藉由Convolutional Neural Networks之影像辨識與提升技術﹙Lab 3﹚。期使學生能夠熟知光電影像處理之原理與系統，以實驗應證這些光電影像的處理；進而運用這些光電影像處理理論與技術，來整合與發展智慧光電影像系統工程。課程內容： 1. Optical Information Processing: (2D Continuous-Space Signal Processing) 4 weeks Lab 1: Optical Character Recognition (OCR) System: Matched Filter and Optical Decorrelation Ref.: J. W. Goodman, Introduction to Fourier Optics, 3rd Ed., Robert ＆amp; Company, 2005. R. Bracewell, The Fourier Transform ＆amp; Its Applications, 3rd Ed., McGraw-Hill, 1999. 2. Digital Image Processing: (2D Discrete-Space Signal Processing) 3 weeks Lab 2: Image Filtering and Restoration with Adaptive Wiener Filter or Image Compression vis SVD Ref.: R. C. Gonzalez and R. E. Woods, Digital Image Processing, 4th Ed., Pearson Education, 2018. MATLAB with Image Processing Toolbox. A. K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 1989. 3. Image Recognition with Deep Learning: 4 weeks Lab 3: Image Recognition and Denoising with Convolutional Neural Networks (Matlab) Ref.: R. C. Gonzalez and R. E. Woods, Digital Image Processing, 4th Ed., Pearson Education, 2018. MATLAB with Deep Learning Toolbox, 2022.

先修科目

修習年級：碩博預修科目：光電工學或訊號處理

教學方式

課程助教：待宣布；電話：(06) 3032121 ext. 57807；E-mail：陽明交大光電學院適應性光子實驗室(Adaptive Photonics Lab., APL) @奇美樓4F R440 備註：上課時間：週五 11:10~12:00 上課地點：奇美樓2F CM215

評分方式

成績計算：總分110分，超過100分以一百分計算 1. 實驗報告(每單元1次，共3次)：20×3=60 2. 期中考試：25 3. 期末考試：25

週次計畫

週次	主題
第 1 週	Off (和平紀念日補假)
第 2 週	Lab 1: Optical Character Recognition (OCR) System
第 3 週	Lab 1: Optical Character Recognition (OCR) System
第 4 週	Lab 1: Optical Character Recognition (OCR) System
第 5 週	Lab 1: Optical Character Recognition (OCR) System
第 6 週	Off (兒童節及民族掃墓節連假)
第 7 週	Lab 2: Image Filtering and Restoration with Adaptive Wiener Filter or Image Compression vis SVD
第 8 週	Mid-Term Exam.
第 9 週	Lab 2: Image Filtering and Restoration with Adaptive Wiener Filter or Image Compression vis SVD
第 10 週	Off (勞動節)
第 11 週	Lab 2: Image Filtering and Restoration with Adaptive Wiener Filter or Image Compression vis SVD
第 12 週	Lab 3: Image Recognition and Denoising with Convolutional Neural Networks (Matlab)
第 13 週	Lab 3: Image Recognition and Denoising with Convolutional Neural Networks (Matlab)
第 14 週	Lab 3: Image Recognition and Denoising with Convolutional Neural Networks (Matlab)
第 15 週	Lab 3: Image Recognition and Denoising with Convolutional Neural Networks (Matlab)
第 16 週	Final Exam.

教科書

1. J. W. Goodman, Introduction to Fourier Optics, 3rd Ed., Robert ＆amp; Company, 2005. R. Bracewell, The Fourier Transform ＆amp; Its Applications, 3rd Ed., McGraw-Hill, 1999. 2. R. C. Gonzalez and R. E. Woods, Digital Image Processing, 4th Ed., Pearson Education, 2018. MATLAB with Image Processing Toolbox. A. K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 1989. 3. R. C. Gonzalez and R. E. Woods, Digital Image Processing, 4th Ed., Pearson Education, 2018. MATLAB with Deep Learning Toolbox, 2022.

Office Hours

地點: @ 奇美樓5F R520
聯絡方式: 電話：(06) 3032121 ext. 57825或0931178072； E-mail: sheanjen@nycu.edu.tw