Efficient computational model for classification of protein localization images using Extended Threshold Adjacency Statistics and Support Vector Machines

摘要

Background and objective: Discriminative and informative feature extraction is the core requirement for accurate and efficient classification of protein subcellular localization images so that drug development could be more effective. The objective of this paper is to propose a novel modification in the Threshold Adjacency Statistics technique and enhance its discriminative power.