Title: IMAGE RECOGNITION METHOD BASED ON DISCRETE WAVELET TRANSFORM (DWT) AND SINGULAR VALUE DECOMPOSITION (SVD)

Year of Publication: 2013
Page Numbers: 42-47
Authors: Mohammad Malakooti, Zahed FerdosPanah, Seyyed Mohsen Hashemi
Conference Name: The Third International Conference on Digital Information Processing and Communications (ICDIPC2013)
- United Arab Emirates

Abstract:


The search for one digital image among the vast quantity of images is a real dilemma when it is based on image content rather than metadata such as eigenvalues or frequency coefficients. The search results for most of the existing methods are satisfactory but still included irrelevant images for the target image. We have introduced a new Image recognition method based on Wavelet Transform (DWT) and Singular Value Decomposition (SVD) that is capable of retrieving most of the images similar to the target image. Our Method used DWT to transfer the target image from the spatial domain into frequency domain in which it is divided into four sub bands, Low-Low (LL), Low-High (LH), High-Low (HL) and High-High (HH) frequencies. We have applied three levels of 2-D DWT to concentrate the image illumination components into the third-level LL sub band and then applied SVD to extract its singular values as the reliable and robust features for the recognition. We also calculated the mean and variance of the low frequency LL sub-band for the input image to create a feature vector composed of mean, variance, and singular values of the LL sub band, as well as the coefficients of the LL sub band. Once the feature vector is formed it is compared with the feature vectors stored in our database to recognize and retrieve the images that are similar to target image based on the minimum error criteria.