Using Phase and Magnitude Information of the Complex Directional Filter Bank for Texture Image Retrieval

Abstract

This paper discusses how to utilize both magnitude and phase information obtained from the complex directional filter bank (CDFB) for the purpose of texture image retrieval. The relative phase, which is the difference of phases between adjacent CDFB coefficients, has a linear relationship with the angle of dominant orientation within a subband. This information is incorporated to form a new feature vector called CDFB-RP. Texture retrieval performance of the proposed CDFB-RP is compared to those of the conventional transforms including the Gabor wavelet, the contourlet transform, the steerable pyramid and the CDFB. With the same number of features, the CDFB-RP method outperforms all other transforms in texture image retrieval, while keeping lower complexity and computational time.