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

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.