Cattle classifications system using Fuzzy K- Nearest Neighbor Classifier

Abstract

This paper presents cattle classifications system using Fuzzy K- Nearest Neighbor Classifier (FKNN). The proposed system consists of two phases; segmentation and feature extraction phase and classifications phase. Expectation Maximization image segmentation (EM) algorithm was used to segments and extracts texture feature of each cattle muzzle image and their image color. Then, it followed by applying the FKNN for classification. The data sets used contains thirty two groups of cattle muzzle images. The experimental result proves the advancement of FKNN classifier better than other classification technique. FKNN achieves 100% classification accuracy compared to 88% classification accuracy achieved from K- Nearest Neighbor Classifier (KNN) classification system.