Texture image retrieval using hybrid directional Extrema pattern
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Texture image retrieval using hybrid directional Extrema pattern Ghanshyam Raghuwanshi 1 & Vipin Tyagi 2 Received: 11 October 2019 / Revised: 30 July 2020 / Accepted: 12 August 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
In this paper, a new descriptor Hybrid Directional Extrema Pattern (HDEP) for the retrieval of texture images by integrating the concept of Weight Difference Directional Local Extrema Pattern (WD_DLEP) and Directional Local Extrema Pattern (DLEP) is proposed. The texture patterns are computed for four principle directions i.e., 0°, 45°, 90°, 135°. The proposed approach considers the difference between central pixel and corresponding neighboring pixels in the specified directions. This difference is used as weight in next stage. This weight is compared with a user-defined threshold to determine the value of strong bits in a feature vector. Experimental evaluation on three benchmark datasets (Brodatz, VisTex and Describable Textures Dataset) illustrates the better performance of proposed system with the other state-of-the-art techniques on two basic parameters i.e., average retrieval rate and time. The proposed approach is evaluated against various state-of-the-art texture image-retrieval systems based on local binary pattern, directional local extrema pattern, local tetra pattern, block-based local binary pattern, center-symmetric local binary pattern and wavelet. Significant improvement has been achieved in image retrieval performance due to assignment of weight in the pattern generation process. Further, the proposed approach is capable of differentiating different texture patterns more efficiently because it uses magnitude of pixel differences to determine the value of current pixel rather than the sign of pixel differences. Keywords Texture patterns . Extrema patterns . Image retrieval . CBIR
* Vipin Tyagi [email protected] Ghanshyam Raghuwanshi [email protected]
1
Manipal University Jaipur, Jaipur, Rajasthan, India
2
Jaypee University of Engineering and Technology, Raghogarh, Guna, MP 473226, India
Multimedia Tools and Applications
1 Introduction With the advancement of high computational facilities, the use of multimedia data is increasing very extensively. This rapid growth in multimedia data throws challenges to the researchers in managing and retrieval of multimedia data from the large databases. Multimedia data includes images and videos. Video retrieval [34] and video captioning [11] are also prime areas of research. The image retrieval systems are classified into text and content-based techniques. In text-based approaches [6, 7, 12], images are annotated using the textual metadata and then retrieved on the basis of textual information. This annotation process is not only laborious and time-consuming, but also depends on the annotator’s perspective. Perspective of a user could be different from the perspective of the annotator which in turn affects the performance of textbased image retrieval techniques. To dea
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