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TRANSCRIPT
Preamble: The purpose of this course is to provide the basic concepts and methodologies for Digital Image Processing in three different levels. At the lowestlevel, the course introduces the terminology of image processing, how digitalimages are generated, how the data is stored, some of the different formats(bmp, gif, tiff, jpeg, etc) and the algorithms deal directly with the raw pixelvalues. In the middle level, it addresses how the algorithm utilizes low levelresults for the processes such as segmentation and edge linking. At highest level,it addresses how the algorithm attempts to extract the semantic information fromthose provided by the lower levels for classification and recognition. Program Outcomes addressed a. Graduates will demonstrate knowledge of mathematics, science andengineering.b. Graduates will demonstrate an ability to identify, formulate and solveengineering problems.f. Graduate will demonstrate skills to use modern engineering tools, softwaresand equipment to analyze problems. Competencies: At the end of the course the student should be able to
1. Describe image acquisition, sampling and quantization 2. Understand different types of image transforms and their properties3. Enhance and restore images in spatial as well as frequency domains4. Segment given images in terms of edge, threshold and region. 5. Apply morphological operations like dilation, erosion, opening and closing ongiven images. 6. Represent, recognize and classify objects from the given images.
IMAGES
acquired by
Image reconstruction done by
are
Digitized by
Formed through
Degraded by
using
EnhancementSampling and Quantization
FourierDFT, FFT, Haar transform, KLT, DCT.
Communication using
Transformed by
Processed for
Spatial Domain
Frequency Domain
Gray Level TransformationHistogram ProcessingSmoothing FiltersSharpening Filters
Smoothing FiltersSharpening Filters
JPEG, MPEGs and H.26x standards, packet video,
Texture X-Ray Computed Tomography
Projections Parallel beam Back projections Fan beam projection Radon transform Fourier-slice theorem,
CBP and FBP methods, ART,
Analysed by
Statistical Approaches Hough Transform, boundary detection, chain coding and segmentation, thresholding methods.
Segmentation
Hough Transform & Chain codes Boundary detection
Thresholding
Applications are
Edge Detection
Done by