Classification of symmetric images by using DoG wavelet
Yuru Zou · Computer Engineering and Applications Journal · 2009
An effective algorithm for detection and classification of cyclic and dihedral symmetric images in DoG wavelet domain is presented.The proposed algorithm is very robust to noise for the noisy images corrupted by Additive White Gaussian Noise(AWGN).Combined with the modified ridgelet transform,the proposed method can successfully detect and classify the noisy im-ages with cyclic and dihedral symmetries,even under the situation of high-level noise(for example,noise deviation is σ=70).