Caricamento in corso...
Principles of digital image processing and technologies (insegnamento su invito)
01RRNRV
A.A. 2025/26
Course Language
Inglese
Degree programme(s)
Doctorate Research in Ingegneria Elettrica, Elettronica E Delle Comunicazioni - Torino
Course structure
| Teaching | Hours |
|---|---|
| Lezioni | 18 |
Lecturers
| Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
|---|
Co-lectures
Context
| SSD | CFU | Activities | Area context | *** N/A *** | 3 |
|---|
This course of image processing will give the student the foundation needed to conduct more advanced work on this topic. Student will use MATLAB throughout the course. MATLAB is the go-to choose for millions of people working in engineering and science and provides the capabilities required to accomplish his image processing tasks.
Discussion of image processing challenges, algorithms and applications
This course of image processing will give the student the foundation needed to conduct more advanced work on this topic. Student will use MATLAB throughout the course. MATLAB is the go-to choose for millions of people working in engineering and science and provides the capabilities required to accomplish his image processing tasks.
Discussion of image processing challenges, algorithms and applications
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Guest Lecture:
Pini Zorea - Braude Engineering College, Haifa, Israel
In this course of digital image processing, student will do first steps in accessing and adjusting digital images for analysis and processing. Student will load, save, and adjust image size and orientation while also understanding how digital images are recognized. Including basic segmentation and quantitative analysis. Student will enhance the image quality of images to make objects of interest easier to identify (e.g., Text detection and recognition, Face detection and recognition).
Guest Lecture:
Pini Zorea - Braude Engineering College, Haifa, Israel
In this course of digital image processing, student will do first steps in accessing and adjusting digital images for analysis and processing. Student will load, save, and adjust image size and orientation while also understanding how digital images are recognized. Including basic segmentation and quantitative analysis. Student will enhance the image quality of images to make objects of interest easier to identify (e.g., Text detection and recognition, Face detection and recognition).
In presenza
On site
Presentazione orale
Oral presentation
P.D.2-2 - Ottobre
P.D.2-2 - October
15/09/2025 9:00–12:00 Lecture 1: Introduction to digital image processing.
Lab 1: Import/export, enhancements, histogram, RGB2GREY, WhatColor intro C Room @DET
16/09/2025 9:00–12:00 Lecture 2: Contrast, Noise Reduction.
Lab 2: CSC, RGB2GREY, brightness & contrast calculations C Room @DET
17/09/2025 9:00–12:00 Lecture 3: Color space conversions.
Lab 3: HSV, background mask, white balance C Room @DET
22/09/2025 14:30–17:30 Lecture 4: Color mask, White balance.
Lab 4: Filters, ROI C Room @DET
25/09/2025 14:30–17:30 Lecture 5: Filters (HPF & LPF), Resize, Crop.
Lab 5: Scaling, segmentation, object counting C Room @DET
26/09/2025 9:00–12:00 Lecture 6: Morphological processing, Segmentation.
Lab 6: Image enhancement for OCR C Room @DET
29/09/2025 14:30–17:30 Lecture 7: Image processing pipeline in Digital Cameras (HW & SW).
Lab 7: Object & face detection C Room @DET
30/09/2025 14:30–17:30 Lecture 8: Image Resize, OCR, Face Detection.
Lecture 8 (cont.): Image quality assessment (Objective & Subjective).
Lab 8: Applications C Room @DET
03/10/2025 9:00–12:00 Final project and course wrap-up C Room @DET
15/09/2025 9:00–12:00 Lecture 1: Introduction to digital image processing.
Lab 1: Import/export, enhancements, histogram, RGB2GREY, WhatColor intro C Room @DET
16/09/2025 9:00–12:00 Lecture 2: Contrast, Noise Reduction.
Lab 2: CSC, RGB2GREY, brightness & contrast calculations C Room @DET
17/09/2025 9:00–12:00 Lecture 3: Color space conversions.
Lab 3: HSV, background mask, white balance C Room @DET
22/09/2025 14:30–17:30 Lecture 4: Color mask, White balance.
Lab 4: Filters, ROI C Room @DET
25/09/2025 14:30–17:30 Lecture 5: Filters (HPF & LPF), Resize, Crop.
Lab 5: Scaling, segmentation, object counting C Room @DET
26/09/2025 9:00–12:00 Lecture 6: Morphological processing, Segmentation.
Lab 6: Image enhancement for OCR C Room @DET
29/09/2025 14:30–17:30 Lecture 7: Image processing pipeline in Digital Cameras (HW & SW).
Lab 7: Object & face detection C Room @DET
30/09/2025 14:30–17:30 Lecture 8: Image Resize, OCR, Face Detection.
Lecture 8 (cont.): Image quality assessment (Objective & Subjective).
Lab 8: Applications C Room @DET
03/10/2025 9:00–12:00 Final project and course wrap-up C Room @DET