Green Image Segmentation Analysis of Google Earth to Rank World Universities using PHP and MATLAB

Project Code :TMMAIN07


The percentage of the green area in each university that is captured by satellite can be used as a world university ranking parameter. In this work, green images taken from Google Earth have been processed through a segmentation stage using HSV threshold method and the details are shared in the website.


This paper describes a novel method for ranking the world universities based on the segmentation techniques. This proposed technique shows that the ranking based on the green area of the universities, the images are taken from Google of universities website. 

Texture segmentation is the process of partitioning an image into regions with different textures containing similar group of pixels. For segmentation purpose, K-means clustering is used to segment an image into regions by extracting the Gabor features and then HSV based thresholding process is performed by converting RGB image into HSV color space which is a simplest method of thresholding images. 

By using Gabor features are extracted for segmenting the clusters. Based on the hue and saturation limitation the green images are analyzed. This research is divided into several processes with the purpose to produce universities ranking based on its greenness and the HSV threshold technique gives better segmentation and accuracy than existing methods.


Keywords: Hue saturation value (HSV), green images, segmentation, thresholding.

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

Block Diagram


Hardware & Software Requirements:

Software: Matlab R2018a.


Operating Systems:

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


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


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 Math Works products may take up to 29 GB of disk space.


Minimum: 4 GB

Recommended: 8 GB

Learning Outcomes

  • Introduction to Matlab
  • 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:
    • Acquisition
    • Image enhancement
    • Image restoration
    • Color image processing
    • Image compression
    •  Morphological processing
    • Segmentation etc.,
  • How to segment the object using Image Processing
  • How to extend our work to another real time applications
  • Project development Skills:
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

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