Title :
A Novel Algorithm of Image Splicing Detection
Author :
Zhu Kaizhen ; Zhen Zhang
Abstract :
Recent advances in computer technology have made digital image tampering more and more common. In this paper we present an approach to passive detection of image splicing. The image splicing detection problem can be regarded as a two-class classification problem under the pattern recognition framework. The features are extracted by image quality metrics (IQMs) and moments of characteristic functions of wavelet subbands. To evaluate the performance of our proposed model, we further present a concrete implementation of this model. Our experimental works have demonstrated that this splicing detection scheme performs effectively and have indicated that the proposed approach possesses promising capability in splicing detection.
Keywords :
computer forensics; feature extraction; image classification; image enhancement; object detection; support vector machines; wavelet transforms; IQM; SVM; characteristic functions; computer generating; computer technology; digital image passive-blind forensics; digital image tampering; feature extraction; image compositing; image enhancement; image morphing; image quality metrics; image rebroadcast; image retouching; image splicing detection problem; made digital image tampering; pattern recognition framework; support vector machine; two-class classification problem; wavelet subbands; Arrays; Feature extraction; Histograms; Image quality; Measurement; Splicing; Support vector machines; Digital image passive-blind forensics; Support Vector Machine (SVM); image quality metrics; image splicing detection; moment based features;
Conference_Titel :
Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4673-1450-3
DOI :
10.1109/ICICEE.2012.512
