New Quantum Inspired Tabu Search for Multi-level Colour Image thresholding

Abstract

In this article, a Quantum Inspired Tabu Search for Multi-level thresholding for Colour Image has been developed to boost the possible effectiveness than that of its classical counterpart. The proposed algorithm has been applied to two true colour images to determine optimal threshold values at different levels using Otsu's method as an objective function. The features of quantum mechanics are coupled with the basic constitution of a popular meta-heuristic algorithm, called tabu search to form the quantum inspired meta-heuristic algorithm. Between the participating algorithms, the proposed algorithm takes least time for execution. The usefulness of the proposed method is established in context of exactitude, resilience and computational time over its respective conventional method. In addition, a popular test, called one-tailed t-test, used for statistical measurement, demonstrates the efficiency of the proposed algorithm.