Title :
Blind Detection of Eclosion Forgeries Based on Curvelet Image Enhancement and Edge Detection
Author :
Qi, Yin-cheng ; Xing, Xiao-shuang ; Zhang, Hua-fang-zi
Author_Institution :
Dept. of Electron. & Commun. Eng., North China Electr. Power Univ., Baoding, China
Abstract :
Digital image forgery is a growing problem as the image could be easily manipulated. Digital image forgery detection has recently received significant attention. A fast and efficient blind detection algorithm is presented for the detection of eclosion forgeries. The second generation of Curvelet transform is firstly used to enhance the image, and then Canny operators is used to detect the edge of the enhanced image, finally the eclosion forgeries can be identified from the edge image. Experimental results show that the algorithm has less operation time and can distinguish the weak edges from the eclosion edges effectively. So it has a higher detection precision and efficiency.
Keywords :
computer forensics; curvelet transforms; edge detection; image coding; image enhancement; Canny operators; blind eclosion forgeries detection; curvelet image enhancement; curvelet transform; digital image forgery; edge detection; Detection algorithms; Forgery; Image edge detection; Image enhancement; Pixel; Transforms; Curvelet transform; eclosion forgery; edge detection; image enhancement;
Conference_Titel :
Multimedia and Signal Processing (CMSP), 2011 International Conference on
Conference_Location :
Guilin, Guangxi
Print_ISBN :
978-1-61284-314-8
Electronic_ISBN :
978-1-61284-314-8
DOI :
10.1109/CMSP.2011.70