TY  - JOUR
T1  - Image Splicing Detection using Uniform Local Binary Pattern and
Wavelet Transform
AU - I. Abd El-Latif, Eman AU - Taha, Ahmed AU - H. Zayed, Hala 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 20
SP  - 7679
EP  - 7684
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.7679.7684
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.7679.7684
KW  - Splicing image forgery
KW  -tampered image detection
KW  -HWT
KW  -ULBP
KW  -SVM
KW  -experiments
AB  - Recently, the problem of detecting image splicing forgery attracts many researchers. Many algorithms
have been presented to deal with this problem. However, most of them suffer from high dimensional feature
vector. In this study, an algorithm is offered to reveal the splicing manipulation in the digital image with size
feature vector. The proposed algorithm is predicated on Haar Wavelet Transform (HWT) and Uniform Local
Binary Pattern (ULBP). The image color space is changed into YCbCr space. This algorithm works on the
chrominance components and HWT is employed to get the four sub-bands. For every sub-band, ULBP is
applied. The last feature vector is generated by merging features from the four sub-bands. Support Vector
Machine (SVM) is used as a classifier. The proposed algorithm is examined on a freely accessible splicing image
datasets (CASIA V1.0 and 2.0). The experiments prove that the proposed algorithm is successful for detecting
the spliced image.
ER  -