A Survey of Analyzing Image Texture Using LBP with k Mean Clustering

Authors

  • Mishra A PG scholar CSE, SDBCE college, RGPV university, Indore, INDIA
  • Sharma N Assistant Professor CSE, SDBCE college RGPV University, Indore, INDIA

Keywords:

CBIR, image retrieval, texture analysis, LBP, segmentation methods

Abstract

The main unit of CBIR ( Content based image retrieval ) is an image retrieval technique that used to retrieve from the database the most similar images to the query image. CBIR is convenient , fast and efficient over image search approaches. In online image retrieval, the user can submit a query to the retrieval system to search for greed images. This paper begins a different and powerful image Texture illustration based on local binary pattern texture features. The input image is divided into several image from which the Local binary pattern feature circulation are clipped and concatenated into an enhanced feature vector. The achievement of the proposed method is determined in the image texture recognition problem under The aim of this work is to find the best way for characterize a given texture using a binary pattern based method. Among given features edge and color evolution are perform by various kind of techniques but for texture analysis there are few method are available .The key objective of the proposed work is to obtain and efficient Algorithm for texture analysis. To find out the hidden texture for a particular given image.

References

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Published

2025-11-11

How to Cite

[1]
A. Mishra and N. Sharma, “A Survey of Analyzing Image Texture Using LBP with k Mean Clustering”, Int. J. Comp. Sci. Eng., vol. 4, no. 5, pp. 172–175, Nov. 2025.

Issue

Vol. 4 No. 5 (2016): IJCSE May Edition

Section

Survey Article

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