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Syllabus of Andhra University MCA - MCA 2.2.5 Image Processing (Elective I)
With effect from 2004-05 admitted batch
Instruction: 3 Periods/week
Sessional Marks: 50
Univ-Exam-Marks:100
Time: 3 Hours
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 onhistogram, 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, propertiesA 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, KIRSCHHomogeneity & DIFF Filters, prewitt filter, Contrast Based edge enhancementtechniques. – 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) -esign of Low pass,High pass, EDGE Enhancement, smoothening filters in Frequency Domain. Butter worthfilter, Homomorphic filters in Frequency Domain Advantages of filters in frequencydomain, 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 dueto 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. Regionbased segmentation methods – segmentation by pixel aggregation, segmentation by subregion aggregation, histogram based segmentation, spilt and merge technique. Use ofmotion 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 by Arthyr –R – Weeks, Jr. (PHI)
2. Image processing, Analysis, and Machine vision by Milan Sonka vaclan Halavac Roger Boyle, Vikas Publishing House.
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