Computer Vision

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.

Discipline(s)

• 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 

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