Digital Image Processing Lecture notes – fall 2008 Lecturer: Conf. dr. ing. Mihaela GORDAN Communications Department e-mail: [email protected].

Digital Image Digital Image ProcessingProcessingLecture notes – fall 2008Lecture notes – fall 2008

Lecturer:Conf. dr. ing. Mihaela GORDANCommunications Departmente-mail: [email protected] phone: 0264-401309Office address: Multimedia (CTMED) laboratory, Str. C. Daicoviciu Nr. 15

Digital Image ProcessingDigital Image Processing

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• Introduction Introduction • Course descriptionCourse description• Exam grade informationExam grade information

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Introduction (1)Introduction (1)

Digital image processing:• deals with digital images = digital representation of the

visual scenes• Note that:Note that: visual perception can be static (scene content unchanged in time) or dynamic (scene content changes in time); the latest case = video sequence;• Typically, visual scene = a static image, a “snap shot”

• tries to:• “implement” in digital (algorithmic) form various human vision processes => image analysis & understanding, pattern recognition• “improve” image appearance for human visualization => image enhancement, de-noising; BASIC IMAGE PROCESSING • store and transmit images efficiently => image compression

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Applications of digital image processing?

… virtually, everywhere!everywhere!

• Industry: inspection/sorting; manufacturing (robot vision)

• Environment: strategic surveillance (hydro-dams, forests, forest fires, mine galleries) by surveillance cameras, autonomous robots

• Medicine: medical imaging (ultrasound, MRI, CT, visible)

• Culture: digital libraries; cultural heritage preservation (storage, restoration, analysis – indexing)

• Television: broadcasting, video editing, efficient storage

• Education & tourism: multi-modal, intelligent human-computer interfaces, with emotion recognition components

• Security/authentication (iris recognition, signature verification) … etc…

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Introduction (3)Introduction (3)

• Industrial inspectionIndustrial inspection(industrial vision systems):(industrial vision systems):

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Introduction (4)Introduction (4)

• Environment surveillance/monitoring:

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Forest fire monitoringHydro sites surveillance

Water sources inspection:

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Introduction (5)Introduction (5)• Medical imaging applications:

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Ultrasound image analysis/quantification

Color image segmentation &Cells counting

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Course description (1)Course description (1)

… Obviously, digital image processing is a very wide field, sooo…

…What will we study in 1 semester…?

• Just the basics you need to develop & implement image processing & analysis algorithms from all the categories above!

• Simplification: - only grey level images - only basic processing methods, without their combination

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Course description (2)Course description (2)

• Course chapters:Course chapters:

I. Grey level digital image representation. Basic math concepts for digital image processing algorithms

II. Grey level image digitization:II. 1. Image sampling II. 2. Image quantization

III. Image transforms: digital image representation in frequency domains; applications: noise filtering, compression, recognition

III. 1. Basic propertiesIII. 2. Sinusoidal transformsIII. 3. Rectangular transformsIII. 4. Eigenvector-based transforms

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Course description (3)Course description (3)IV. Image enhancement:

IV. 1. Point operations IV. 2. Grey level histogram; histogram-based enhancement IV. 3. Spatial operations IV. 4. Transform-based operations IV. 5. Color image enhancement & pseudo-coloring

V. Image analysis & understanding:V.1. Regions of interest; features; feature extractionV. 2. Edge detection, boundary extraction & representationV. 3. Regions detection, extraction & representationV. 4. Binary object structure analysis & representation: median axis transforms; binary morphology

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Course description (4)Course description (4)V. 5. Shape descriptorsV. 6. Texture representation; texture descriptorsV. 7. Region-based image segmentation

VI. Image compression & coding:VI. 1. IntroductionVI. 2. Pixel codingVI. 3. Predictive coding of still imagesVI. 4. Transform coding of still imagesVI. 5. Video sequence (inter-frame) coding

… all with practical examples given – in the lectures & lab!

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Exam grade informationExam grade information

• The grade components:1) Written exam – quiz: => max. 3.5 pts

- 6 questions from theory- 6 questions from problems/exercises

2) Written exam – classic: => max. 6.5 pts - 5 short theoretic subjects (max. ½ page answer)- 5 problems/exercises

=> Written exam grade E=1…103) Laboratory work evaluation: => grade L=1…10 4) Lecture participation/discussions: => grade LD=1…105) Project evaluation: => grade P=1…10

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The grade = 0.75(0.7E+0.2L+0.1LD)+0.25PTo pass the exam: must have E≥ 5, L≥ 5.

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