Texture Based Image Segmentation Using Image Processing Techniques

Project Code :TMMAIP404

Objective

Texture based segmentation using image processing techniques like grayscale conversion, morphological operations, boundary plotting etc.

Abstract

Texture segmentation is a vital part of texture analysis. Its goal is to determine the borders between multiple textured sections in an image dynamically. We present a morphological technique for textured image segmentation in this work. First, we'll look at the fundamental step of evaluating local entropy of grayscale image. We also perform morphological operations on texture image. Finally, we overlay a boundary line by dividing the textured border with the help of finding perimeters of the binary objects.

Keywords: Texture segmentation, Morphological operations, Image segmentation, Image processing

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Software: Matlab 2018 or above

Hardware:

Operating Systems:

  • Windows 10
  • Windows 7 Service Pack 1
  • Windows Server 2019
  • Windows Server 2016

Processors:

Minimum: Any Intel or AMD x86-64 processor

Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support

Disk:

Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation

Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space

RAM:

Minimum: 4 GB

Recommended: 8 GB

Learning Outcomes

·   Introduction to Matlab

·   What is EISPACK & LINPACK

·   How to start with MATLAB

·   About Matlab language

·   Matlab coding skills

·   About tools & libraries

·   Application Program Interface in Matlab

·   About Matlab desktop

·   How to use Matlab editor to create M-Files

·   Features of Matlab

·   Basics on Matlab

·   What is an Image/pixel?

·   About image formats

·   Introduction to Image Processing

·   How digital image is formed

·   Importing the image via image acquisition tools

·   Analyzing and manipulation of image.

·   Phases of image processing:

               o  Acquisition

               o  Image enhancement

               o  Image restoration

               o   Color image processing

               o  Image compression

               o   Morphological processing

               o   Segmentation etc.,

·   How to extend our work to another real time applications

·   Project development Skills

               o   Problem analyzing skills

               o   Problem solving skills

               o   Creativity and imaginary skills

               o   Programming skills

               o   Deployment

               o   Testing skills

               o   Debugging skills

               o   Project presentation skills

               o   Thesis writing skills

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