Periods/week : 3 Periods & 1 Tut /week.                                                                  Ses. : 30 Exam : 70 Examination (Practical): 3hrs.                                                                                   Credits: 4

1. Fundamentals of Image Processing
Image Acquisition, Image Model, Sampling, Quantization, Relationship between pixels,     distance measures, connectivity , Image Geometry, Photographic  film.  Histogram: Definition, decision of contrast basing on histogram, operations basing on  histograms like image stretching, image sliding, Image classification.   Definition and Algorithm of Histogram equalization.
2. Image Transforms:-
A detail discussion on Fourier Transform, DFT,FFT, properties. A brief discussion on WALSH Transform , WFT, HADAMARD Transform, DCT.
3.  Image Enhancement: (by SPATIAL Domain Methods)
a )Arithmetic and logical operations, pixel or point operations, size operations,  b.   Smoothing filters- Mean, Median, Mode filters – Comparative study,  c..  Edge enhancement filters – Directorial filters, Sobel, Laplacian, Robert, KIRSCH, Homogeneity & DIFF Filters, prewitt filter, Contrast Based edge
enhancement techniques.  Comparative study.  d.  Low Pass filters, High Pass filters, sharpening filters. – Comparative Study.  e.   Comparative study of all filters.  f.  Color image processing.
4. Image enhancement : (By  FREQUENCY Domain Methods).  Design of Low pass, High pass, EDGE Enhancement, smoothening filters in Frequency   Domain. Butter worth filter, Homomorphic filters in Frequency Domain. Advantages of filters in frequency domain, comparative study of filters in frequency domain  and spatial domain.
5. Image compression: Definition,  A brief discussion on – Run length encoding, contour coding,  Huffman code,  compression due to change in domain, compression due to quantization, Compression at the time of image transmission.  Brief discussion on:- Image Compression standards.
6. Image Segmentation: Definition, characteristics of segmentation. Detection of Discontinuities, Thresholding   Pixel based segmentation method.  Region based segmentation methods – segmentation by pixel aggregation, segmentation by    sub region aggregation, histogram based segmentation, spilt and merge technique. Use of motion in segmentation (spatial domain technique only)
7. Morphology:-
Dilation, Erosion, Opening, closing, Hit-and-Miss transform, Boundary extraction,
Region filling, connected components, thinning, Thickening, skeletons , Pruning
Extensions to Gray – Scale Images Application of Morphology in I.P

Text Book:
Digital Image Processing , Rafael C. Gonzalez and   Richard E. Woods, Addision Wesley
Reference books:
1.            Fundamentals of Electronic Image Processing ,Arthur .R. Weeks, Jr. (PHI)
2.            Image processing, Analysis, and Machine vision, Milan Sonka , Vaclav Hlavac, Roger Boyle, Vikas Publishing House.

tejus mahiCSE 3.2 SyllabusImage Processing Syllabus
Periods/week : 3 Periods & 1 Tut /week.                                                                  Ses. : 30 Exam : 70 Examination (Practical): 3hrs.                                                                                   Credits: 4 1. Fundamentals of Image Processing Image Acquisition, Image Model, Sampling, Quantization, Relationship between pixels,     distance measures, connectivity...