Abstract
In the technical period, things will enrich it every day, one of which is content-based image retrieval. The comparative study of texture-dependent algorithms based on a spatial domain with feature extraction and distance metrics was explored in this paper. Texture attribute extraction uses the gray level co-occurrence matrix and local binary pattern for statistical analysis. The correlation test shows that contrast, correlation, energy, entropy, and homogeneity feature of gray level co-occurrence matrix and local binary pattern features taken from the LBP histogram have a significant correlation. For the study of the gray level co-occurrence vector and local binary pattern on content-based image retrieval system, the precision, accuracy, and recall as well as F-score are measured.
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Dolly, B., Raj, D. (2021). Texture Based Image Retrieval Using GLCM and LBP. In: Bhattacharyya, S., Nayak, J., Prakash, K.B., Naik, B., Abraham, A. (eds) International Conference on Intelligent and Smart Computing in Data Analytics. Advances in Intelligent Systems and Computing, vol 1312. Springer, Singapore. https://doi.org/10.1007/978-981-33-6176-8_5
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DOI: https://doi.org/10.1007/978-981-33-6176-8_5
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