{"product_id":"9789365210873-1","title":"Digital Image Processing for GTU 24 Course (V - CSE(AI\u0026ML)\/AI\u0026ML - BE05000191)","description":"\u003cp\u003eSyllabus Digital Image Processing - (BE05000191) Total Credits  = TH\/30 \tAssessment Pattern and Marks\t Total Marks \tTheory\tTutorial \/ Practical\t \tESE (E)\tPA (M)\tPA (I)\tPBL (I)\tESE (V)\t 04\t70\t30\t20\t30\t50\t200  Sr. No.\tContent    1.\tIntroduction to Digital Image Processing What is Digital Image Processing? Origins and history of digital image processing Fields that use digital image processing (Medical, Remote Sensing, Forensics, etc.) Fundamental steps in digital image processing Components of an image processing system (Chapter - 1)    2.\tDigital Image Fundamentals Elements of visual perception Light and the electromagnetic spectrum Image sensing and acquisition Image sampling and quantization Basic relationships between pixels (neighbors, adjacency, connectivity) Basic mathematical tools (linear vs. non-linear operations, arithmetic\/logic operations) (Chapter - 2)   3.\tIntensity Transformations and Spatial Filtering Basic intensity transformation functions (log, power-law, contrast stretching) Histogram processing (equalization, specification\/matching) Fundamentals of spatial filtering and filter mechanics Smoothing (lowpass) spatial filters : mean, Gaussian, order-statistics Sharpening (high pass) spatial filters : Laplacian, unsharp masking, high-boost. (Chapters - 3, 4)    4.\tFiltering in the Frequency Domain Fourier series and Fourier transform background Sampling and the Fourier transform of sampled functions Discrete Fourier Transform (DFT) - 1D and 2D Properties of the 2-D DFT and IDFT Image smoothing using lowpass frequency domain filters (Ideal, Butterworth, Gaussian) Image sharpening using high pass filters Selective filtering : band reject and bandpass filters Fast Fourier Transform (FFT) - efficiency and implementation. (Chapters - 5, 6)   5.\tColor Image Processing Color fundamentals : tristimulus values, chromaticity Color models : RGB, CMY\/CMYK, HSI, HSV, Lab Pseudo color image processing Basics of full-color image processing Color transformations and color balance Color image smoothing and sharpening (Chapter - 7)  6.\tWavelet and Other Image Transforms Matrix-based transforms (basis vectors and images) Discrete Cosine Transform (DCT), Walsh-Hadamard Transform Haar Transform Wavelet transforms : multiresolution analysis, fast wavelet transform 2-D wavelet transforms and sub band coding (Chapter - 8)   7.\tMorphological Image Processing Structuring elements, erosion and dilation Opening and closing operations Hit-or-miss transform Morphological algorithms : boundary extraction, region filling, thinning, pruning Morphological reconstruction Grayscale morphology. (Chapter - 9)   8.\tImage Segmentation Fundamentals of image segmentation Edge detection : point, line, and edge detectors (Sobel, Prewitt, Canny, Laplacian of Gaussian) Thresholding : global, variable, and multivariable thresholding; Otsu's method Region-based segmentation : growing, splitting, and merging K-means clustering, super pixels Graph-cut segmentation Morphological watersheds (Chapter - 10)\u003c\/p\u003e","brand":"Technical Publications","offers":[{"title":"Default Title","offer_id":48215665934507,"sku":"12146151302","price":995.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0620\/3355\/9723\/files\/9789365210873_1_83a0e1c5-28e8-4f7a-9dd2-5882141bd395.jpg?v=1791616584","url":"https:\/\/technicalpublications.in\/products\/9789365210873-1","provider":"Technical Publications","version":"1.0","type":"link"}