Abstract
Gray-level co-occurrence matrix (GLCM) is one of the oldest techniques used for texture analysis. It has two important parameters, i.e., distance and direction. In this paper, various combinations of distance and directional angles used for GLCM calculation are analyzed in order to recognize certain patterned images based on their textural features. In the proposed approach, the work is divided into two modules: determining the pattern of the image and pattern retrieval from the dataset. Patterns considered in this paper are horizontal striped, vertical striped, right and left diagonally striped, checkered and other images. For recognizing the pattern, the proposed approach has achieved a percentage accuracy of 96, 98, 96, 90, 96 and 94 for horizontal striped, vertical striped, right and left diagonally striped, checkered and other irregular patterns (not fully stripped), respectively. The proposed approach has a practical implementation in the fashion industry so to filter the search according to the pattern of the cloth.
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We, the authors of the paper, certify that we have no affiliations with or involvement in any organization or entity with any financial interest (such as honorary; educational grants), in the materials discussed in this manuscript. Also we would like to bring to your kind notice that this manuscript is an extended version of the paper titled GLCM and its applications in Pattern Recognition, presented in ISCBI-17 Conference, held in Dubai during AUGUST 9–11, 2017. The paper is also available online. http://ieeexplore.ieee.org/document/8053537/.
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Srivastava, D., Rajitha, B., Agarwal, S. et al. Pattern-based image retrieval using GLCM. Neural Comput & Applic 32, 10819–10832 (2020). https://doi.org/10.1007/s00521-018-3611-1
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DOI: https://doi.org/10.1007/s00521-018-3611-1