In this paper, we proposed a new texture image retrieval method based on discrete non-separable shearlet transform (DNST) domain local neighborhood intensity pattern (LNIP), which can fully characterize the discriminative information among ...

Neither a single local feature nor a single global feature can completely characterize image information, and fusion of two or more complementary features can effectively improve retrieval performance in image retrieval. In this paper, a texture ...

In the deep texture image retrieval, to address the problem that the retrieval performance is affected by the lack of sufficiently large texture image dataset used for the effective training of deep neural network, a deep learning based texture dataset ...

This paper proposes a novel technique for texture image retrieval based on tetrolet transforms. Tetrolets provide fine texture information due to its different way of analysis. Tetrominoes are applied at each decomposition level of an image and best ...

In this paper, a simple and an efficient Content Based Image Retrieval which is based on orthogonal polynomials model is presented. This model is built with a set of carefully chosen orthogonal polynomials and is used to extract the low level texture ...

In this paper, we develop a new approach which exploits the probabilistic properties from the phase information of 2-D complex wavelet coefficients for image modeling. Instead of directly using phases of complex wavelet coefficients, we demonstrate why ...

In this paper, we present a novel method, which uses non-separable wavelet filter banks, to extract the features of texture images for texture image retrieval. Compared to traditional tensor product wavelets (such as db wavelets), our new method can ...

This paper presents a novel approach for personal identification based on a wavelet-based fingerprint retrieval system which encompasses three image retrieval tasks, namely, feature extraction, similarity measurement, and feature indexing. We propose ...