![]() ![]() IEEE Signal Process Mag 30(2):87–96īreiman L (1996) Bagging predictors. In: Proceedings of 12th international conference on document analysis and recognition, Washington, DC, pp 6–110īianchi T, Piva A (2013) Secure watermarking for multimedia content protection: a review of its benefits and open issues. Digit Investig 5(1):49–59īertrand R, Gomez-Kramer P, Terrades OR, Franco P, Ogier JM (2013) A system based on intrinsic features for fraudulent document detection. In: Proceedings of international conference on image processing, Genova, Italy, vol 3, pp 69–78īayram S, Sencar HT, Memon N (2008) Classification of digital camera-models based on demosaicing artifacts. In: Proceedings of 3rd Rapidminer community meeting and conference, Aachen, Germany, pp 1–12īayram S, Sencar H, Memon N, Avcibas I (2005) Source camera identification based on CFA interpolation. In: Proceedings of non-impact printing and digital fabrication conference, Salt Lake City, Utah, vol 1, pp 301–305Īmer M, Goldstein M (2012) Nearest-neighbor and clustering based anomaly detection algorithms for Rapidminer. The proposed model has achieved the best accuracy of 95.1% using a combination of KPNF + ORB + SURF with random forest classifier and adaptive boosting methodology.Īli GN, Mikkilineni AK, Delp EJ, Allebach JP, Chiang PJ, Chiu GT (2004) Application of principal components analysis and gaussian mixture models to printer identification. Further, adaptive boosting and bootstrap aggregating methodologies are used for the improvement in classification accuracy. The document classifier proposed model can efficiently classify the questioned documents to their respective printer class. Then, feature-based classifiers are implemented using K-NN, decision tree, random forest and majority voting. Hand-crafted features based on key printer noise features (KPNF), speeded up robust features (SURF) and oriented FAST rotated and BRIEF (ORB) are used. This paper aims to fix the document source printer using passive approach. Other techniques look for the irregularities present in the document. ![]() ![]() Most of the passive techniques aim to detect and fix the source of the printed document. Other documents need passive approach for document forensics. Critical documents are protected using watermarks or signatures, i.e., active approach. Document forgery has increased enormously due to the progression of information technology and image processing software. ![]()
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