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PX5525: IMAGE ANALYSIS (2024-2025)

Last modified: 23 Aug 2024 16:16


Course Overview

Nowadays a large volume of data is stored in form of images. This course introduces the tools needed to analyse images and extract information from them, including aspects of image enhancement, filtering, segmentation, morphological analysis and image classification based on convolutional neural networks.

Course Details

Study Type Postgraduate Level 5
Term Second Term Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr M. Carmen Romano

What courses & programmes must have been taken before this course?

  • Any Postgraduate Programme (Studied)

What other courses must be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

The main focus of the course is to introduce key concepts of image analysis. Emphasis will be put on the concepts underlying the algorithms to analyse images, including image enhancement, filtering (spatial and frequency domain), segmentation, morphological transformations, colour image analysis and convolutional neural networks for automatic classification of images. During the lectures, the main concepts and ideas will be explained, and during the practical sessions, we will discuss how to implement the algorithms to apply them to images.  This course will therefore provide students with the fundamentals of how to process and extract information from images.


Details, including assessments, may be subject to change until 30 August 2024 for 1st term courses and 20 December 2024 for 2nd term courses.

Summative Assessments

Class Test

Assessment Type Summative Weighting 34
Assessment Weeks Feedback Weeks

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Weighting: 1/3 (33.33...%)

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualUnderstandDevelop an understanding of the fundamental mathematical principles underlying audio and image analysis.
ProceduralEvaluateDevelop the abilities needed to critically compare different tools and approaches of audio and image analysis and chose the ones better suited for a given task.
ProceduralUnderstandIdentify basic concepts, terminology and methods in the field of digital audio and image analysis.

Class Test

Assessment Type Summative Weighting 33
Assessment Weeks 31 Feedback Weeks 33

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Weighting: 1/3 (33.33...%)

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualUnderstandDevelop an understanding of the fundamental mathematical principles underlying audio and image analysis.
ProceduralApplyBe able to carry out standard segmentation, filtering, recognition and other basic procedures of audio and video data analysis.

Class Test

Assessment Type Summative Weighting 33
Assessment Weeks 31,32,33 Feedback Weeks 31,32,33

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Weighting: 1/3 (33.33...%)

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualUnderstandDevelop an understanding of the fundamental mathematical principles underlying audio and image analysis.
ProceduralApplyBe able to carry out standard segmentation, filtering, recognition and other basic procedures of audio and video data analysis.
ProceduralUnderstandIdentify basic concepts, terminology and methods in the field of digital audio and image analysis.

Formative Assessment

There are no assessments for this course.

Resit Assessments

Online Test

Assessment Type Summative Weighting 100
Assessment Weeks Feedback Weeks

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ProceduralUnderstandIdentify basic concepts, terminology and methods in the field of digital audio and image analysis.
ProceduralApplyBe able to carry out standard segmentation, filtering, recognition and other basic procedures of audio and video data analysis.
ConceptualUnderstandDevelop an understanding of the fundamental mathematical principles underlying audio and image analysis.
ProceduralEvaluateDevelop the abilities needed to critically compare different tools and approaches of audio and image analysis and chose the ones better suited for a given task.

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