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Review on Local Binary Patterns Variants as Texture Descriptors for Copy-Move Forgery Detection

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@article{IJASEIT3396,
   author = {Rafidah Muhamad and Azurah Abu Samah and Hairudin Abdul Majid and Ghazali Sulong and Mohd Saberi Mohamad and Shahreen Kasim},
   title = {Review on Local Binary Patterns Variants as Texture Descriptors for Copy-Move Forgery Detection},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {7},
   number = {5},
   year = {2017},
   pages = {1678--1684},
   keywords = {LBP variants; feature extraction; digital image forgery; copy-move},
   abstract = {

Past decades had seen the concerned by researchers in authenticating the originality of an image as the result of advancement in computer technology. Many methods have been developed to detect image forgeries such as copy-move, splicing, resampling and et cetera. The most common type of image forgery is copy-move where the copied region is pasted on the same image. The existence of high similarity in colour and textures of both copied and pasted images caused the detection of the tampered region to be very difficult. Additionally, the existence of post-processing methods makes it more challenging. In this paper, Local Binary Pattern (LBP) variants as texture descriptors for copy-move forgery detection have been reviewed. These methods are discussed in terms of introduction and methodology in copy-move forgery detection. These methods are also compared in the discussion section. Finally, their strengths and weaknesses are summarised, and some future research directions were pointed out.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=3396},    doi = {10.18517/ijaseit.7.5.3396} }

EndNote

%A Muhamad, Rafidah
%A Abu Samah, Azurah
%A Abdul Majid, Hairudin
%A Sulong, Ghazali
%A Mohamad, Mohd Saberi
%A Kasim, Shahreen
%D 2017
%T Review on Local Binary Patterns Variants as Texture Descriptors for Copy-Move Forgery Detection
%B 2017
%9 LBP variants; feature extraction; digital image forgery; copy-move
%! Review on Local Binary Patterns Variants as Texture Descriptors for Copy-Move Forgery Detection
%K LBP variants; feature extraction; digital image forgery; copy-move
%X 

Past decades had seen the concerned by researchers in authenticating the originality of an image as the result of advancement in computer technology. Many methods have been developed to detect image forgeries such as copy-move, splicing, resampling and et cetera. The most common type of image forgery is copy-move where the copied region is pasted on the same image. The existence of high similarity in colour and textures of both copied and pasted images caused the detection of the tampered region to be very difficult. Additionally, the existence of post-processing methods makes it more challenging. In this paper, Local Binary Pattern (LBP) variants as texture descriptors for copy-move forgery detection have been reviewed. These methods are discussed in terms of introduction and methodology in copy-move forgery detection. These methods are also compared in the discussion section. Finally, their strengths and weaknesses are summarised, and some future research directions were pointed out.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=3396 %R doi:10.18517/ijaseit.7.5.3396 %J International Journal on Advanced Science, Engineering and Information Technology %V 7 %N 5 %@ 2088-5334

IEEE

Rafidah Muhamad,Azurah Abu Samah,Hairudin Abdul Majid,Ghazali Sulong,Mohd Saberi Mohamad and Shahreen Kasim,"Review on Local Binary Patterns Variants as Texture Descriptors for Copy-Move Forgery Detection," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 5, pp. 1678-1684, 2017. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.7.5.3396.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Muhamad, Rafidah
AU  - Abu Samah, Azurah
AU  - Abdul Majid, Hairudin
AU  - Sulong, Ghazali
AU  - Mohamad, Mohd Saberi
AU  - Kasim, Shahreen
PY  - 2017
TI  - Review on Local Binary Patterns Variants as Texture Descriptors for Copy-Move Forgery Detection
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 7 (2017) No. 5
Y2  - 2017
SP  - 1678
EP  - 1684
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - LBP variants; feature extraction; digital image forgery; copy-move
N2  - 

Past decades had seen the concerned by researchers in authenticating the originality of an image as the result of advancement in computer technology. Many methods have been developed to detect image forgeries such as copy-move, splicing, resampling and et cetera. The most common type of image forgery is copy-move where the copied region is pasted on the same image. The existence of high similarity in colour and textures of both copied and pasted images caused the detection of the tampered region to be very difficult. Additionally, the existence of post-processing methods makes it more challenging. In this paper, Local Binary Pattern (LBP) variants as texture descriptors for copy-move forgery detection have been reviewed. These methods are discussed in terms of introduction and methodology in copy-move forgery detection. These methods are also compared in the discussion section. Finally, their strengths and weaknesses are summarised, and some future research directions were pointed out.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=3396 DO - 10.18517/ijaseit.7.5.3396

RefWorks

RT Journal Article
ID 3396
A1 Muhamad, Rafidah
A1 Abu Samah, Azurah
A1 Abdul Majid, Hairudin
A1 Sulong, Ghazali
A1 Mohamad, Mohd Saberi
A1 Kasim, Shahreen
T1 Review on Local Binary Patterns Variants as Texture Descriptors for Copy-Move Forgery Detection
JF International Journal on Advanced Science, Engineering and Information Technology
VO 7
IS 5
YR 2017
SP 1678
OP 1684
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 LBP variants; feature extraction; digital image forgery; copy-move
AB 

Past decades had seen the concerned by researchers in authenticating the originality of an image as the result of advancement in computer technology. Many methods have been developed to detect image forgeries such as copy-move, splicing, resampling and et cetera. The most common type of image forgery is copy-move where the copied region is pasted on the same image. The existence of high similarity in colour and textures of both copied and pasted images caused the detection of the tampered region to be very difficult. Additionally, the existence of post-processing methods makes it more challenging. In this paper, Local Binary Pattern (LBP) variants as texture descriptors for copy-move forgery detection have been reviewed. These methods are discussed in terms of introduction and methodology in copy-move forgery detection. These methods are also compared in the discussion section. Finally, their strengths and weaknesses are summarised, and some future research directions were pointed out.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=3396 DO - 10.18517/ijaseit.7.5.3396