Texture analysis and retrieval using fractal signature and B-spline wavelet transform with second order derivative

In the paper, we proposed a novel over-complete B-spline wavelet transform and fractal signature for texture image analysis and retrieval. Traditionally, discrete wavelet frame took the first order derivative of smoothing function into account, which is equivalent to Canny edge detection. The second order derivative spline wavelet has the ability to detect the variation of the edge width, and the finite impulse response is conducted in the paper. Additionally, statistical features in wavelet domain and fractal signature are utilized in the retrieval. Experimental results have shown that the proposed method is reasonable to describe the essences of the textures and can reach the highest retrieval rate (76.54%) comparing with Gabor Filter and first order derivative over-complete wavelet transform.