NDLI: Co-occurrence matching of local binary patterns for improving visual adaption and its application to smoke recognition

Content Provider	IET Digital Library
Author	Yuan, Feiniu Shi, Jinting Xia, Xue Huang, Qinghua Li, Xuelong
Abstract	It is challenging to recognize smoke from visual scenes due to large variations of smoke colors, textures and shapes. To improve robustness, we propose a novel feature extraction method based on similarity and dissimilarity matching measures of Local Binary Patterns (LBP). Given two bit-sequences of an LBP code pair, the similarity and dissimilarity matching measures are defined as the ratios of the 1–1 bitwise matching number to the 0–0 bitwise matching number and the 1–0 number to the 0–1 number, respectively. To capture local code variations, we calculate the measures between LBP codes of a center pixel and its neighbors. Then we compare each measure with its global mean to propose Similarity Matching based Local Binary Patterns (SMLBP) and Dissimilarity Matching based Local Binary Patterns (DMLBP). Since SMLBP and DMLBP extract spatial variations of the 1st order LBP codes, they actually represent the 2nd order variations of pixel values. Furthermore, we adopt different mapping modes and multi-scale neighborhoods to obtain rotation and scale invariances. Finally, we concatenate the histograms of LBP, SMLBP and DMLBP to generate a feature vector containing 1st and 2nd order information. Experiments show that our method obviously outperforms existing methods.
Starting Page	178
Ending Page	187
Page Count	10
ISSN	17519632
Volume Number	13
e-ISSN	17519640
Issue Number	Issue 2, Mar (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/13/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2018.5164
Journal	IET Computer Vision
Publisher Date	2018-07-25
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	1-1 Bitwise Matching Number-to-the-0-0 Bitwise Matching Number Algebra Bit-sequences Centre Pixel Co-occurrence Matching Computer Vision And Image Processing Technique Dissimilarity Matching Measure Dissimilarity Matching-based Local Binary Pattern DMLBP Feature Extraction Final Feature Vector Generation First-order Information First-order LBP Code Image And Video Coding Image Classification Image Coding Image Colour Analysis Image Matching Image Recognition Image Representation Image Resolution Image Texture LBP Code Pair Mapping Mode Multiscale Neighbourhoods Object Recognition Pixel Value Rotation Invariance Scale Invariance Second-order Information Second-order Variation Representation Similarity Matching Measure Similarity Matching-based Local Binary Pattern SMLBP Smoke Smoke Colours Smoke Dataset Smoke Recognition Smoke Shapes Smoke Textures Spatial Variation Extraction Texture Classification Texture Dataset Vector Visual Adaption Visual Scenes
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Binary pattern matching from a local dissimilarity measure

Some variants of spiral LBP in texture recognition

Using colour local binary pattern features for face recognition

Optimized rotation invariant content based image retrieval with local binary pattern

A Completed Modeling of Local Binary Pattern Operator for Texture Classification

A comparative study of factors affecting performance of local binary pattern (lbp) variant along with distance metrics for face recognition.

Learning Multi-scale Block Local Binary Patterns for Face Recognition

Local binary pattern-based seabed image texture discrimination.

Compact descriptor for local feature using dominating centre-symmetric local binary pattern

Co-occurrence matching of local binary patterns for improving visual adaption and its application to smoke recognition

Similar Documents

Binary pattern matching from a local dissimilarity measure

Some variants of spiral LBP in texture recognition

Using colour local binary pattern features for face recognition

Optimized rotation invariant content based image retrieval with local binary pattern

A Completed Modeling of Local Binary Pattern Operator for Texture Classification

A comparative study of factors affecting performance of local binary pattern (lbp) variant along with distance metrics for face recognition.

Learning Multi-scale Block Local Binary Patterns for Face Recognition

Local binary pattern-based seabed image texture discrimination.

Compact descriptor for local feature using dominating centre-symmetric local binary pattern

Co-occurrence matching of local binary patterns for improving visual adaption and its application to smoke recognition