MATLAB ADVANCED Level-II

  • 02 Months
  • IV  Sem

  • Er. Vivek Yadav

Introduction of Course :

In this value addition course “MATLAB ADVANCED Level-II” we have focused on the all basics aspect of signal processing. This course provides valuable knowledge and experience to our students about image analysis in MATLAB. Learning and analyzing Skills of students can be enhanced using this course. The course would be covered under theory and laboratory. In addition to assigning small project–based learning, early exposure to hands-on Signal Processing Tool Box in MATLAB, to enhance the practical skills among the students This course includes the fundamentals of various image Transforms, Image Enhancement Techniques, Image restoration Techniques and methods, image compression and Segmentation used in digital image processing.

Upon successful completion of this course, the student should be able to:

  • Analysis and improve the quality of digital image which can be processed in MATLAB. 
  • Perform the analysis of the different Image using segmentation techniques.
  • Learn the different feature extraction methods and apply them in the image processing problem areas.
  • Do the research in the field of image processing using MATLAB.

Course Plan:

S.No. Topics Contents
1.  Introduction Introduction and Fundamentals, Motivation and Perspective, Applications, Components of Image Processing System.
2.  Image Processing Some basic concepts, Image appears in the Workspace Reading an image, Finding dimensions, Basic Commands of RGB Model, image Conversion. RGB to Grayscale Image Conversion, RGB to HSV Image Conversion. 
3.  Implementation of Image Filters Basic Concepts, Implementation of Image Filters, Edge-Preserving Image Filter.
4.  Noise Basic Concepts of Remove .Image Noise, Noise Reduction Implementation, Add Noise to Image
5.  Image Enhancement Image Enhancement in Spatial Domain: Basic Gray Level Functions
6.  Gray Level Functions Introduction; Basic Gray Level Functions
7.  Piecewise Linear Transformation Functions Piecewise-Linear Transformation Functions: Contrast, Stretching
8.  Histogram Specification Histogram Specification; Histogram Equalization;
9.  Spatial Filtering Basics of Spatial Filtering; Smoothing – Mean filter,
10.  Edge and Line Detection Edge and Line Detection: Edge Detection, Edge Operators,