IT6005 DIP Notes, Digital Image Processing Lecture Handwritten Notes – ECE 7th SEM

IT6005 DIP Notes

Anna University Regulation 2013 ECE IT6005 DIP Notes, Digital Image Processing Engineering Lecture Handwritten Notes for all 5 units are provided below. Download link for ECE 7th SEM IT6005 Digital Image Processing Engineering Lecture Handwritten Notes are listed down for students to make perfect utilization and score maximum marks with our study materials.

IT6005                         DIGITAL IMAGE PROCESSING                            L T P C 3 0 0 3

OBJECTIVES:

The student should be made to:

 Learn digital image fundamentals.

 Be exposed to simple image processing techniques.

 Be familiar with image compression and segmentation techniques.

 Learn to represent image in form of features.

UNIT I DIGITAL IMAGE FUNDAMENTALS 8

Introduction – Origin – Steps in Digital Image Processing – Components – Elements of Visual Perception – Image Sensing and Acquisition – Image Sampling and Quantization – Relationships between pixels – color models.

UNIT II IMAGE ENHANCEMENT 10

Spatial Domain: Gray level transformations – Histogram processing – Basics of Spatial Filtering– Smoothing and Sharpening Spatial Filtering – Frequency Domain: Introduction to Fourier Transform – Smoothing and Sharpening frequency domain filters – Ideal, Butterworth and Gaussian filters.

UNIT III IMAGE RESTORATION AND SEGMENTATION 9

Noise models – Mean Filters – Order Statistics – Adaptive filters – Band reject Filters – Band pass Filters – Notch Filters – Optimum Notch Filtering – Inverse Filtering – Wiener filtering Segmentation: Detection of Discontinuities–Edge Linking and Boundary detection – Region based segmentation- Morphological processing- erosion and dilation.

UNIT IV WAVELETS AND IMAGE COMPRESSION 9

Wavelets – Subband coding – Multiresolution expansions – Compression: Fundamentals – Image Compression models – Error Free Compression – Variable Length Coding – Bit-Plane Coding – Lossless Predictive Coding – Lossy Compression – Lossy Predictive Coding – Compression Standards.

UNIT V IMAGE REPRESENTATION AND RECOGNITION 9

Boundary representation – Chain Code – Polygonal approximation, signature, boundary segments – Boundary description – Shape number – Fourier Descriptor, moments- Regional Descriptors – Topological feature, Texture – Patterns and Pattern classes – Recognition based on matching.

TOTAL: 45 PERIODS

OUTCOMES:

Upon successful completion of this course, students will be able to:

 Discuss digital image fundamentals.

 Apply image enhancement and restoration techniques.

 Use image compression and segmentation Techniques.

 Represent features of images.

TEXT BOOK:

1. Rafael C. Gonzales, Richard E. Woods, “Digital Image Processing”, Third Edition, Pearson Education, 2010.

REFERENCES:

1. Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, “Digital Image Processing Using MATLAB”, Third Edition Tata Mc Graw Hill Pvt. Ltd., 2011.

2. Anil Jain K. “Fundamentals of Digital Image Processing”, PHI Learning Pvt. Ltd., 2011.

3. Willliam K Pratt, “Digital Image Processing”, John Willey, 2002.

4. Malay K. Pakhira, “Digital Image Processing and Pattern Recognition”, First Edition, PHI Learning Pvt. Ltd., 2011.

5. http://eeweb.poly.edu/~onur/lectures/lectures.html

6. http://www.caen.uiowa.edu/~dip/LECTURE/lecture.html

IT6005 DIP Unit notes  Download Here

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Related Links

For IT6005 DIP Previous Year Question Papers – Click here

For IT6005 DIP Question Bank/2marks 16marks with answers – Click here

For IT6005 DIP Important Questions/Answer Key – Click here

 

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One comment

  1. Ramanathan Niranjana

    im not able to download the dip handwritten notes. the link loops back to the same page .plz do help me to get the notes

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