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 applicationsL2: Image types, color systems, operationsL3: Filters: Mean, Gaussian, median filters. Blurring images, and other operationsL4: Fourier transform, Law pass filters, high pass filters, deblurring, noise eliminationL5: Frequency filters, comparison between spatial domain and frequency domainL6: Morphological operationsL7: Edge detectionL8: SegmentationL9: Intro to deep learning, neural networksL10: intro to CNN for computer vision, Object segmentation and classification using CNN.PW1: image basics using OpenCV libraryPW2: Blinding and pasting images, some operations, CV functions.PW3: Image ThresholdingPW4: Blurring and smoothingPW5: Morphological operationsPW6: GradientsPW7: Corner detectionPW8: Edge detectionPW9: Licence plate detection and blurringPW10: Face detection