Comparative Analysis of Proposed Methods for Analysing Color Pixel based Image Segmentation Using Tiger Image Dataset

Abstract

Image segmentation is a plays the vital role of image partitioning into multiple region (pixel clustering). The aim of segmentation is to obtain a new image in which it is easy to detect regions of
interest, localize objects, or determine characteristic features such as edges. Image segmentation is one of the important methods to classify the pixels of an image correctly in a decision oriented application. It divides an image into a number of discrete regions such that the pixels have high similarity in each region and high contrast between regions. Segmentation is the partition of a digital image into regions to simplify the image representation into something that is more meaningful and easier to analyze. Considering that an image can be regarded as a tiger image dataset in which each pixel has a spatial location and a color value, color image segmentation can be obtained by clustering these pixels into different groups of coherent spatial connectivity and color. Conservation of tiger has been the challenging task. This work would add a small account to the herculean task of conserving the species. This work proposes an algorithm from which the age of the tiger can be inferred. This work combines the domain of image processing with data mining to infer the age of tiger. This research work proposes a method to find the age of the tiger, using color as a parameter. Color pixel based image classification and clustering techniques has been used to identify the age of the tiger.