JOURNAL ARTICLE

A local adaptive image descriptor

S. M. Zahid IshraqueMohammad ShoyaibM. Abdullah‐Al‐WadudMd. Monirul HoqueOksam Chae

Year: 2013 Journal:   New Review of Hypermedia and Multimedia Vol: 19 (3-4)Pages: 286-298   Publisher: Taylor & Francis

Abstract

The local binary pattern (LBP) is a robust but computationally simple approach in texture analysis. However, LBP performs poorly in the presence of noise and large illumination variation. Thus, a local adaptive image descriptor termed as LAID is introduced in this proposal. It is a ternary pattern and is able to generate persistent codes to represent microtextures in a given image, especially in noisy conditions. It can also generate stable texture codes if the pixel intensities change abruptly due to the illumination changes. Experimental results also show the superiority of the proposed method over other state-of-the-art methods.

Keywords:
Local binary patterns Artificial intelligence Pattern recognition (psychology) Noise (video) Image (mathematics) Pixel Computer science Computer vision Texture (cosmology) Binary number Image texture Simple (philosophy) Mathematics Histogram Image processing

Metrics

8
Cited By
0.26
FWCI (Field Weighted Citation Impact)
18
Refs
0.64
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Analysis and Summarization
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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