Region Duplication Detection Using Image Feature Matching

Pan, Xunyu; Lyu, Siwei

doi:10.1109/tifs.2010.2078506

Cited by 367 publications

(251 citation statements)

References 34 publications

Supporting

Mentioning

238

Contrasting

Unclassified

Order By: Relevance

“…Then we reported the highest detection accuracy which was for the 32×32 blocks. The techniques we used for comparison were by Chen et al [5] and Pan and Lyu [14]. Both techniques are robust and yield very good results.…”

Section: Resultsmentioning

confidence: 99%

“…Classification is then performed using an SVM classifier. Pan and Lyu [14] extract SIFT features then determine duplicate regions based on a feature matching technique. Similarly, Chen et al [5] present a method that detects Harris corner interest points in an image, then statistical analysis is performed to represent image regions around Harris points.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Forgery Localization Based on Image Chroma Feature Extraction

Alfraih¹,

Briffa²,

Wesemeyer³

2013

5th International Conference on Imaging for Crime Detection and Prevention (ICDP 2013)

View full text Add to dashboard Cite

Many passive image tamper detection techniques have been presented in the expanding field of image forensics. Some of these techniques use a classifier for a final decision based on whole image statistics, resulting in a lack of forgery localization. The aim of this paper is to add localization to a previously published algorithm that uses grey-level co-occurrence matrix (GLCM) for extracting texture features from the chromatic component of an image (Cb or Cr component). Experimental results show that we can localize tampering for different sized regions with reasonable accuracy. The main trade-off is a diminishing detection accuracy as the region size decreases.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Forgery Localization Based on Image Chroma Feature Extraction

Alfraih¹,

Briffa²,

Wesemeyer³

2013

5th International Conference on Imaging for Crime Detection and Prevention (ICDP 2013)

View full text Add to dashboard Cite

show abstract

“…Image feature matching approach [62]  Visual of the restored images is better than conventional fixedsize block-based approach.…”

Section: Region Based Duplicationmentioning

confidence: 99%

Detection of Image Tampering over Diverse information Security Schemata: A State-of-the-Art

Pande¹,

Patil²,

Bhattacharya³

2014

IJCA

View full text Add to dashboard Cite

Many recent technologies in the field of image processing have necessitated the attention to the field of image forensics. Increase in cyber communication system and availability of advanced digital processing tools, in the past decades has given birth to forgery attempts. Irrespective of various approaches used to protect the Image, proving integrity of the image received in communication is a difficult issue. Under such circumstances, no image can be treated secure against breaches. Moreover, knowledge of the manipulation model is a must for detecting a certain type of tampering.The aim of this paper is to highlight new developments regarding detection of tampering in comparison of various schemata used in the past decades for forgery detection. An assortment of various models used for providing information security to image based on authentication, integrity and confidentiality is presented. Methods of tamper detection have been assessed over the type of attack. An in depth classification of types of image security has been proposed which emphasizes total security issues. The paper puts forward chief developments in schemata of tampering detection. General Terms

show abstract

“…Pan et al [5] reported in 2004 that edge direction information can be utilized for detecting blocking artifacts. Author presented a novel unreferenced approach which is irrespective of the exact location of block boundary and therefore invariant to translation, scaling and rotation of the images.…”

Section: Introductionmentioning

confidence: 99%

Forensics, Anti-forensics and Counter Anti-forensics for JPEG Compressed Images

2016

IJCCIE

View full text Add to dashboard Cite

Abstract---With the advancement in information technology and image processing software the manipulation of the images has increased considerably from past few decades. Retouching or tampering of the images has been so prevalent that nowadays one can hardly believe their originality. Image authenticity is done using forgery detection techniques. These methods are broadly classified as active and passive. Aim of this paper is to give state of art for a passive detection technique i.e. JPEG double compression. Its forensics, anti-forensics and counter anti-forensics is presented with a review of technologies that exist so far.

show abstract

Region Duplication Detection Using Image Feature Matching

Cited by 367 publications

References 34 publications

Forgery Localization Based on Image Chroma Feature Extraction

Forgery Localization Based on Image Chroma Feature Extraction

Detection of Image Tampering over Diverse information Security Schemata: A State-of-the-Art

Forensics, Anti-forensics and Counter Anti-forensics for JPEG Compressed Images

Contact Info

Product

Resources

About