Open AccessVariants of Local Binary Pattern: A Review
Author(s) -
Aditya Singh,
Ramesh Kumar Sunkaria,
Anterpreet Kaur Bedi
Publication year - 2021
Publication title -
aijr proceedings
Language(s) - English
Resource type - Conference proceedings
ISSN - 2582-3922
DOI - 10.21467/proceedings.114.21
Subject(s) - local binary patterns , image texture , artificial intelligence , pixel , computer science , computer vision , binary image , image segmentation , pattern recognition (psychology) , image retrieval , texture (cosmology) , segmentation , binary number , image (mathematics) , feature detection (computer vision) , image processing , histogram , mathematics , arithmetic
In everyday life, image data, such as information, processing and computer vision, play a significant role in many applications; such as image classification, image segmentation and image retrieval. A preferred attributes that has been applied in a lots of picture applications is texture. This was forming an image using an array of pixels. Texture played a significant part in image segmentation and image detection and retrieval. In addition ranked the classifications of the texture then local binary pattern are coming. The LBP method seemed to work very effectively in real time. In the LBP method, comparing the values of the central pixels with the values of the neighbouring pixels and to attribute the binary values on these values. In this paper providing an overview for the local binary model and their benefits.