ANNA UNIVERSITY ECE SYLLABUS
IT6005 DIGITAL IMAGE PROCESSING SYLLABUS
COMMON FOR CSE,ECE,IT DEPARTMENTS
REGULATION 2013
 |
| IT6005 DIGITAL IMAGE PROCESSING SYLLABUS |
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.
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
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
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
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
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
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.
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
No comments:
Post a Comment