Title
LPQ++: A discriminative blur-insensitive textural descriptor with spatial-channel interaction
Abstract
Effective texture categorization plays an important role in effective visual recognition. Despite noticeable progress in this area, blurred-texture recognition remains a challenge. As a key reason for this, existing well-established visual descriptors (e.g., local binary patterns and deep convolutional feature) generally cannot ensure an insensitivity to blur, exhibiting a considerable decrease in performance under clear to blurring conditions. To alleviate this, we propose a discriminative blur-insensitive textural descriptor, referred to as local phase quantization plus plus (LPQ++). The main idea is to establish spatial-channel interactions between the normalized blur-insensitive feature maps yielded by a short-term Fourier transform (STFT) to enhance the descriptive power while maintaining the insensitivity to blur. In particular, spatial interactions executed within the specific STFT feature map capture the spatial correlations between neighboring points. Meanwhile, the column-wise channel interactions among the STFT feature maps help differentiate the edge and flat areas in the images; this is crucial for effective texture characterization under blurring conditions. To enable blurred texture description under dense sampling conditions, LPQ++ is extracted by calculating the spatial-channel gradient orientation histogram and embedding it into the Fisher vector. Experiments conducted on three difficult texture datasets demonstrate the effectiveness of LPQ++ for blurred-texture categorization. Our code is open-source and available at https://github.com/hustzhzhu/LPQplusplus.
Year
DOI
Venue
2021
10.1016/j.ins.2020.10.006
Information Sciences
Keywords
DocType
Volume
Blurred-texture categorization,Short-term Fourier transform,Spatial-channel interaction,Fisher vector,LPQ++
Journal
548
ISSN
Citations 
PageRank 
0020-0255
0
0.34
References 
Authors
33
6
Name
Order
Citations
PageRank
Zihao Zhu100.34
Yang Xiao223726.58
Shuai Li3176.90
Zhiguo Cao431444.17
Zhiwen Fang5142.25
Joey Tianyi Zhou635438.60