Description

Image processing is a fundamental aspect of computer science and engineering, focusing on the analysis and manipulation of digital images using algorithms and mathematical techniques. This course provides students with a comprehensive understanding of image processing concepts, techniques, and applications. In addition, this course covers an introduction about computer vision goals, challenges and applications and an intro to deep learning.

Disciplines

• Informatique

Syllabus

L1: Introduction to computer vision, intro to image processing and its applications

L2: Image types, color systems, operations

L3: Filters: Mean, Gaussian, median filters. Blurring images, and other operations

L4: Fourier transform, Law pass filters, high pass filters, deblurring, noise elimination

L5: Frequency filters, comparison between spatial domain and frequency domain

L6: Morphological operations

L7: Edge detection

L8: Segmentation

L9: Intro to deep learning, neural networks

L10: intro to CNN for computer vision, Object segmentation and classification using CNN.

PW1: image basics using OpenCV library

PW2: Blinding and pasting images, some operations, CV functions.

PW3: Image Thresholding

PW4: Blurring and smoothing

PW5: Morphological operations

PW6: Gradients

PW7: Corner detection

PW8: Edge detection

PW9: Licence plate detection and blurring

PW10: Face detection 

MCC

Les épreuves indiquées respectent et appliquent le règlement de votre formation, disponible dans l'onglet Documents de la description de la formation.

Régime d'évaluation

ECI (Évaluation continue intégrale)

Coefficient

1.0

Évaluation initiale / Session principale - Épreuves