Template matching using chaotic imperialist competitive algorithm

Image matching plays an important role in feature tracking, object recognition, stereo matching, digital photogrammetry, remote sensing, and computer vision. Imperialist competitive algorithm (ICA) is inspired by imperialistic competition mechanism. In this paper, we present a novel template matching method based on chaotic ICA. Based on the introduction of the principle of ICA, the correlation function used in this approach is proposed. The chaos can improve the global convergence of ICA, and the phenomena of falling into local best solution can be prevented. The detailed process for chaotic ICA-based template matching is also presented in detail. The three typical comparative results show that our proposed chaotic ICA image matching approach is more efficient and effective than the basic ICA.