Sampling and Quantisation of Digital image

 

Digital Image Processing LAB

 Syllabus

Software Testing

Syllabus

Unit 1: Principles of Testing, Software development life cycle model: Phases of software project, Quality, Quality assurance and quality control, Testing, Verification and validation, Process models to represent various phases, Life cycle models, Software testing life cycle. Click Here White Box Testing (WBT) and Black Box Testing: Static testing, Structural testing, Challenges in WBT. PPT1 Black box testing: Black box testing process. PPT2     PPT3

UNIT II Integration Testing: Definition, As a type of testing: Top-down integration, Bottom-up integration, Bidirectional integration, System integration, Choosing integration method, As a phase of testing, Scenario testing: System scenarios, Use case scenarios, Defect bash. PPT Extra PPT

UNIT III System and Acceptance Testing: Functional Vs non Functional, Functional system testing, Non-functional system testing, Acceptance testing. PPT (Unit III, Unit IV, Unit V)

UNIT IV Performance testing, Regression testing, Internationalization testing, Adhoc testing: Factors governing performance of testing, Methodology, tools and process for performance testing. Regression Testing: Introduction, Types of Regression testing, Regression testing process. Adhoc testing: Introduction, Buddy testing, Pair testing, exploratory testing, Iterative testing, Agile and Extreme testing, XP work flow, Defect seeding. Adhoc Testing (PPT)

UNIT V Testing Object-Oriented Software: Introduction, Comparison of object oriented and procedural software, System testing example, Unit testing of classes, Tools for testing object oriented software, Testing web applications.

Question Bank (New 20-05-2023)

Question Bank (New 20-05-2023)

Question Bank

Digital Image Processing

 Syllabus

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UNIT I Image fundamentals: Image acquisition, sampling and quantization, image resolution,

Videos :Click here

 basic relationship between pixels,

Videos : click here

 color images, RGB, HSI and other models.

Videos: click here 

Questions on Color Model

PPT (Unit 1)  (by Prof. P. Ulhe)

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Unit II: Two dimensional transforms: 2D-Discrete fourier transform, discrete cosine transform, Walsh Hadamard transform, Haar transform, KL transform, and discrete wavelet transform.

Question bank Unit 1 and Unit 2

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Unit 3:
 Spatial domain Processing: Point processing such as digital negative, contrast stretching, thresholding, gray level slicing, bit plane slicing, log transform and power law transform, neighbourhood processing such as averaging filters, order statistics filters, high pass filters and high boost filters, histogram equalization and histogram specification, frequency domain such as DFT for filtering, ideal, Gaussian and butterwort filters for smoothening and sharpening, and homomorphic filters.
File 2: Question bank
unit 3 ppt (by prof Vishal Moyal)

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Unit 4:
Image segmentation and morphology: Point, line and edge detection, edge linking using Hough transform and graph theoretic approach, thresholding, and region based segmentation, dilation, erosion, opening, closing, hit or miss transform, thinning and thickening, and boundary extraction on binary images.
File 4 Question bank
File 5 Question Bank
unit 4 ppt (by prof Vishal Moyal)

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Unit 5: Degradation model, noise models, estimation of degradation function by modelling, restoration using Weiner filters and inverse filters. File 6:

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Unit 6: Video formation, perception and representation: Digital video sampling, video frame classifications, I, P and B frames, notation, ITU-RBT 601 digital video formats, digital video quality measure, video capture and display: principle of colour video camera, video camera, digital video, sampling of video signals: required sampling rates, sampling in two dimensions and three dimensions, progressive virus interlaced scans, two dimensional motion estimation, block matching algorithms. Q.1 What are the required sampling rates for video signals?  Explain video sampling in three dimensions. Q.2 classifications of video frames Full Reference: https://nptel.ac.in/courses/117/104/117104020/

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Digital Image Processing Lab Syllabus

 Course Title: Digital Image Processing Lab 

Semester VI 

Course Code BTITL608 

Course Type Mandatory 

Pre-requisite OOP with C++ 

L – T – P 0 – 0 – 2 Stream 

Core Credits 1 

Lab Experiments List: Study of “Matlab/Scilab or any other open source Image Processing Toolbox” and experiments as per the syllabus, to be decided by the concerned faculty.

Software Testing Syllabus

Course Title: Software Testing (Semester VI) Course Code: BTITPE603A Course Type: Elective Prerequisite: Software Engineering L – T – P: 3 – 0 – 0 Stream: Software Application & Development Credits: 3

Course Objectives:

1. Study fundamental concepts in software testing, including objectives, processes, criteria, strategies, and methods.
2. Learn test project planning, test case and test data design, test operations, software problem management, defect handling, and test reporting.
3. Develop an understanding of quality and its importance in software systems and development processes.
4. Study issues and techniques for implementing and managing software quality assurance processes and procedures.

Course Outcomes: Upon completion of the course, students should be able to:

1. Apply software testing knowledge and processes to software applications.
2. Identify software testing problems.
3. Solve software testing problems by designing and selecting test models, criteria, strategies, and methods.
4. Apply learned techniques to improve software development quality.
5. Prepare a software quality plan for a software project.

Course Contents: UNIT I: Principles of Testing

• Software development life cycle model
• Phases of software project
• Quality, quality assurance, and quality control
• Testing, verification, and validation
• Process models and life cycle models
• Software testing life cycle
• White Box Testing (WBT) and Black Box Testing

UNIT II: Integration Testing

• Definition and types of integration testing
• Top-down integration, bottom-up integration, bidirectional integration, system integration
• Choosing integration method
• Scenario testing

UNIT III: System and Acceptance Testing

• Functional vs non-functional testing
• Functional system testing
• Non-functional system testing
• Acceptance testing

UNIT IV: Performance, Regression, and Internationalization Testing

• Performance testing: methodology, tools, and process
• Regression testing: types and process
• Internationalization testing
• Adhoc testing: introduction and techniques

UNIT V: Testing Object Oriented Software and Web Applications

• Comparison of object-oriented and procedural software
• Testing object-oriented software: system and unit testing
• Tools for testing object-oriented software
• Testing web applications

Textbook:

1. Srinivasan Desikan, Gopalaswamy Ramesh, "Software Testing: Principles and Practices", Pearson publication, 2nd Edition, 2006.

Reference Books:

1. Louise Tamres, "Introducing Software Testing", Pearson publication, 2002.
2. Boris Beizer, "Software Testing Techniques", Dreamtech press, 2nd Edition, 2014.

Digital Image Processing Syllabus

 Course Title: Digital Image Processing 

Semester VI 

Course Code BTITC604 

Course Type Elective 

Pre-requisite

L – T – P - 3 – 0 – 0 

Stream Core Credits 3

Course Objectives: 1. To cover the fundamentals and mathematical models in digital image and video processing. 2. To develop time and frequency domain techniques for image enhancement. 3. To expose the students to current technologies and issues in image and video processing. 4. To develop image and video processing applications in practice. 

Course Outcomes: At the end of this course, students will be able to: 1. Understand theory and models in Image and Video Processing. 2. Interpret and analyze 2D signals in frequency domain through image transforms. 3. Apply quantitative models of image and video processing for various engineering applications. 4. Develop innovative design for practical applications in various fields. 

Course Content: 

UNIT I Image fundamentals: Image acquisition, sampling and quantization, image resolution, basic relationship between pixels, color images, RGB, HSI and other models. 

UNIT II Two dimensional transforms: 2D-Discrete fourier transform, discrete cosine transform, Walsh Hadamard transform, Haar transform, KL transform, and discrete wavelet transform. 

UNIT III Spatial domain Processing: Point processing such as digital negative, contrast stretching, thresholding, gray level slicing, bit plane slicing, log transform and power law transform, neighbourhood processing such as averaging filters, order statistics filters, high pass filters and high boost filters, histogram equalization and histogram specification, frequency domain such as DFT for filtering, ideal, Gaussian and butterwort filters for smoothening and sharpening, and homomorphic filters. 

UNIT IV Image segmentation and morphology: Point, line and edge detection, edge linking using Hough transform and graph theoretic approach, thresholding, and region based segmentation, dilation, erosion, opening, closing, hit or miss transform, thinning and thickening, and boundary extraction on binary images. 

UNIT V Degradation model, noise models, estimation of degradation function by modelling, restoration using Weiner filters and inverse filters. 

UNIT VI Video formation, perception and representation: Digital video sampling, video frame classifications, I, P and B frames, notation, ITU-RBT 601 digital video formats, digital video quality measure, video capture and display: principle of colour video camera, video camera, digital video, sampling of video signals: required sampling rates, sampling in two dimensions and three dimensions, progressive virus interlaced scans, two dimensional motion estimation, block matching algorithms. 

Text Books: 1. Gonzales and Woods, "Digital Image Processing", Pearson Education, India, Third Edition. 2. Anil K.Jain, "Fundamentals of Image Processing", Prentice Hall of India, First Edition, 1989. 

Reference Books: 1. Ze-Nian Li and Mark S. Drew, "Fundamentals of Multimedia", PHI 2011. 2. Murat Tekalp, "Digital Video Processing", Pearson, 2010. 3. John W. Woods, "Multidimensional Signal, Image and Video Processing", Academic Press 2012. 6. A.I.Bovik, "Handbook on Image and Video Processing", Academic Press.