article · 2025

Local Binary Patterns: Spatial Encoding to Deep Learning Fusion

Vandana Gupta, Ashish Mishra, Nishant Shrivastava

Cited by 0Abstract and details only

Abstract

Local Binary Pattern (LBP) is a popular and important handcrafted method that is used to extract local structural information from images. It is very simple and fast in computation, which makes it suitable for texture classification tasks and for systems that need to work in real time or with limited resources. LBP and its variations are very useful in many computer vision applications such as image retrieval, object detection, medical image analysis, and face recognition. This work reviews the main developments in LBP-based methods with emphasis on the variants developed in the spatial domain. These versions were introduced to handle issues such as noise, changes in lighting, and the lack of rotation invariance. This study also shows that LBP-based methods continue to be effective, discriminative, and practical for real-world applications.

Cite this paper

APA 7

Gupta, V., Mishra, A., & Shrivastava, N. (2025). Local Binary Patterns: Spatial Encoding to Deep Learning Fusion. https://doi.org/10.1109/iciip68302.2025.11346255

MLA 9

Gupta, Vandana, et al. “Local Binary Patterns: Spatial Encoding to Deep Learning Fusion.” 2025, pp. 267–72, https://doi.org/10.1109/iciip68302.2025.11346255.

Chicago

Gupta, Vandana, Ashish Mishra, and Nishant Shrivastava. 2025. “Local Binary Patterns: Spatial Encoding to Deep Learning Fusion.” https://doi.org/10.1109/iciip68302.2025.11346255.

Harvard

Gupta, V., Mishra, A. and Shrivastava, N. (2025) ‘Local Binary Patterns: Spatial Encoding to Deep Learning Fusion’. Available at: https://doi.org/10.1109/iciip68302.2025.11346255.

BibTeX

@article{gupta2025local,
  title = {{Local Binary Patterns: Spatial Encoding to Deep Learning Fusion}},
  author = {Gupta, Vandana and Mishra, Ashish and Shrivastava, Nishant},
  pages = {267--272},
  year = {2025},
  doi = {10.1109/iciip68302.2025.11346255}
}

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