EC60501: Digital Image Processing
| EC60501 | |||||||||||||||||||||||||
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| Course name | Digital Image Processing | ||||||||||||||||||||||||
| Offered by | Electronics & Electrical Communication Engineering | ||||||||||||||||||||||||
| Credits | 4 | ||||||||||||||||||||||||
| L-T-P | 3-1-0 | ||||||||||||||||||||||||
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| Semester | Autumn | ||||||||||||||||||||||||
Syllabus
Syllabus mentioned in ERP
Pre-requisites: EC31008Digital image fundamentals: Visual perception, image sensing and acquisition, sampling and quantization, basic relationship between pixels and their neighborhood properties; Image enhancement in spatial domain: Gray-level transformations, histogram equalization, spatial filters- averaging, order statistics; Edge detection: first and second derivative filters, Sobel, Canny, Laplacian and Laplacian-of Gaussion masks; Image filtering in frequency domain: One and two-dimensional DFT, properties of 2-D DFT, periodicity properties, convolution and correlation theorems, Fast Fourier Transforms, Smoothing and sharpening filtering in frequency domain, ideal and Butterworth filters, homomorphic filtering; Image restoration: Degradation/ restoration process, noise models, restoration in presence of noise-only spatial filtering, linear position-invariant degradations, estimating the degradation function, inverse filtering, Wiener filtering, constrained least squares filtering, geometric transformations; Color image processing: Color models âÃÂàRGB, HSI, YUV, pseudo-color image processing, full-color image processing, color transformation, color segmentation, noise in color images; Morphological Image Processing: Basic operations- dilation, erosion, opening, closing, Hit-Miss transformations, Basic morphological algorithms- boundary extraction, region filling, connected components, convex hull, thinning, thickening, skeletons, pruning, extensions to gray-scale morphology; Image segmentation: Edge linking and boundary detection, Hough transforms, graph-theoretic techniques, global and adaptive thresholding, Region based segmentation, Segmentation by morphological watersheds, motion based segmentation; Texture Analysis: Cooccurrence matrix, Gabor filter.
Concepts taught in class
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Classroom resources
Additional Resources
Time Table
| Day | 8:00-8:55 am | 9:00-9:55 am | 10:00-10:55 am | 11:00-11:55 am | 12:00-12:55 pm | 2:00-2:55 pm | 3:00-3:55 pm | 4:00-4:55 pm | 5:00-5:55 pm | |
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| Monday | R302 | |||||||||
| Tuesday | ||||||||||
| Wednesday | R302 | R302 | ||||||||
| Thursday | R302 | |||||||||
| Friday |