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Texture image retrieval using DNST domain local neighborhood intensity pattern

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Abstract

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 particular coefficient and its adjacent neighbors within a local window. Firstly, the original image is decomposed into different subbands of frequency and orientation responses by using discrete non-separable shearlet transform (DNST). Secondly, based on center symmetric-local binary pattern theory, the sign and magnitude patterns of DNST domain LNIP descriptor are constructed using novel computation rule. Meanwhile, a new binary bit-string encoding scheme is developed, which can overcome the information redundant and inaccurate problem of conventional encoding strategy in LNIP. Thirdly, the mean, standard deviation and entropy values of the DNST domain LNIP at different scales are calculated and fused into a vector as the image texture feature values, which effectively reduce the feature dimensions. And finally, image similarity measurement is accomplished by using closed-form solutions for the Kullback–Leibler divergences between the DNST domain LNIP based image texture features. Experimental results on some test images and comparison with well-known existing methods demonstrate the efficacy and superiority of the proposed method.

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Acknowledgments

This work was supported partially by the National Natural Science Foundation of China (Nos. 61472171 & 61701212), Scientific Research Project of Liaoning Provincial Education Department (No. LJKZ0985), and Natural Science Foundation of Liaoning Province (No. 2019-ZD-0468).

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  1. School of Computer and Information Technology, Liaoning Normal University, Dalian, 116029, People’s Republic of China

    Xiangyang Wang, Hongying Yang, Siyang Gao & Panpan Niu

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  1. Xiangyang Wang
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Correspondence to Xiangyang Wang or Hongying Yang.

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Wang, X., Yang, H., Gao, S. et al. Texture image retrieval using DNST domain local neighborhood intensity pattern. Multimed Tools Appl 81, 29525–29554 (2022). https://doi.org/10.1007/s11042-022-12819-x

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