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42042 - Artificial Vision (VA) [URV]


Type: S3 Course
Semester: Fall
ECTS: 4.5
Teaching Points:
Offer: Annual
Responsible Unit: URV
Responsible: Domènec Puig
Language: English
Requirements:

GOALS

This course aims at studying the fundamental techniques for image processing and advanced issues on machine vision related to the problems of automatic analysis and recognition of complex images. Practical applications will be developed on well-known machine vision software.


CONTENTS

1. Image Processing.
  • Filtering and smoothing operations. Morphological techniques.
2. Feature Extraction.
  • Lines and corners detection. Identification of basic geometrical structures.
3. Color and texture analysis.
  • Color models, kinds of texture, texture feature extraction, geometrical methods.
4. Image Segmentation and Image Classification.
  • Unsupervised segmentation based on regions and edges. Supervised classification, theoretical decision methods, statistical methods, neural networks.
5. Stereoscopic Vision.
  • Camera calibration and camera systems, epipolar geometry, image rectification, search for correspondences, triangulation.
6. Perception and 3D Modeling.
  • Range images generation, extraction of geometric elements, automatic scene generation, scene recognition, geometrical hashing.