Fast and robust passive copy-move forgery detection using SURF and SIFT image features

Pandey, Ramesh Chand; Singh, Sanjay Kumar; Shukla, K. K.; Agrawal, Rishabh

doi:10.1109/iciinfs.2014.7036519

Cited by 40 publications

(17 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Zhang et al [Zhang, Yang, Niu et al (2017)] presented a method which combined SURF with FMT algorithm. This method resolved the issue in Lin et al [Lin and Wu (2011); Hashmi, Anand and Keskar (2014); Pandey, Singh, Shukla et al (2015)]. In summary, SURF techniques have a higher overall performance than SIFT techniques because of the lower dimension of descriptors.…”

Section: Surf Techniquesmentioning

confidence: 94%

“…At the same time, they replaced DWT with DyWT to strengthen the robustness of translation. Pandey et al [Pandey, Singh, Shukla et al (2015)] proposed a method based on SURF and SIFT. The forged areas can be localized quickly and accurately.…”

Section: Surf Techniquesmentioning

confidence: 99%

“…The forged areas can be localized quickly and accurately. However, the methods proposed in Lin et al [Lin and Wu (2011); Hashmi, Anand and Keskar (2014); Pandey, Singh, Shukla et al (2015)] cannot localize smooth areas ineffectively. Zhang et al [Zhang, Yang, Niu et al (2017)] presented a method which combined SURF with FMT algorithm.…”

Section: Surf Techniquesmentioning

confidence: 99%

See 2 more Smart Citations

A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques

Tan¹,

Wu²,

Wu³

et al. 2019

Journal of New Media

View full text Add to dashboard Cite

Digital images can be tampered easily with simple image editing software tools. Therefore, image forensic investigation on the authenticity of digital images' content is increasingly important. Copy-move is one of the most common types of image forgeries. Thus, an overview of the traditional and the recent copy-move forgery localization methods using passive techniques is presented in this paper. These methods are classified into three types: block-based methods, keypoint-based methods, and deep learning-based methods. In addition, the strengths and weaknesses of these methods are compared and analyzed in robustness and computational cost. Finally, further research directions are discussed.

show abstract

Section: Surf Techniquesmentioning

confidence: 94%

Section: Surf Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques

Tan¹,

Wu²,

Wu³

et al. 2019

Journal of New Media

View full text Add to dashboard Cite

show abstract

“…Una técnica de localización y detección de eliminación de objetos es la que se nos presenta en [16]. Se utilizó aquí Scale-Invariant Feature Transform (SIFT) junto con la coincidencia k-NN y correlación cruzada ruido-residuo para detectar falsificaciones copia-pega.…”

Section: Iii-b Detección De Manipulación Intra-fotogramaunclassified

Técnica de Detección de Manipulación en Vídeos Digitales Basada en los Algoritmos de Compresión

Fernández¹,

Orozco²,

Villalba³

2020

Seguridad Informática. X Congreso Iberoamericano, CIBSI 2020

View full text Add to dashboard Cite

Resumen-Las imágenes y vídeos digitales juegan un papel muy importante en la vida cotidiana. A día de hoy, la mayor parte de la población es poseedora de cámaras fotográficas de última generación integradas en su dispositivo móvil. El desarrollo tecnológico no sólo facilita la generación de contenido multimedia, sino también la manipulación intencionada de éste, y es aquí donde las técnicas forenses de detección de manipulación sobre imágenes y vídeos cobran gran importancia. En este trabajo se proponen dos metodologías forenses basadas en algoritmos de compresión: La primera de ellas trata de detectar la presencia de recompresión en un vídeo digital mediante el análisis de sus macrobloques, característica propia del estándar H.264-MPEG4. Posteriormente, se utiliza la máquina de soporte vectorial para crear el modelo que permita la verificación del número de recompresiones de un vídeo. La segunda metodología que se explica en este trabajo tiene por objetivo detectar alteraciones de tipo 'empalme', es decir, regiones que no pertenecen al contenido original de una imagen digital, técnica que está basada en la tasa de error que introduce el algoritmo de compresión JPEG cada vez que recomprime una imagen.

show abstract

“…Some researchers such as Arandjelovic et al [14] introduced a new method by using Rootsift for object retrieval in large scale image dataset. Pandey et al [35] designed a method that uses SURF and SIFT robust in detecting copymoved regions. Prasad et al [36] compared the SURF and hybrid features such as SURF-HOG and SIFT-HOG, Histogram of Oriented Gradients (HOG), and the copy-move forgery detection using image features like SIFT, Lee [37] provided a new image searching method extracting features and combine Advanced Speed up Robust Feature (ASURF) and Domain Color Descriptor (DCD).…”

Section: Related Workmentioning

confidence: 99%

Exploring Rotation and Scale Invariant Features in Image Pla- giarism Detection Using Manifold-Ranking Algorithm

Jahangard¹

2018

IJET

View full text Add to dashboard Cite

Plagiarism, as a crucial offense especially in academia, not only is well-known problem in text but also is becoming widespread in image. In this work, the performance of manifold-ranking, known as robust method among semi-supervised methods, has been investigated by using twelve different features. As its high performance is attributed to the quality of constructed graph, we applied robust k-regular nearest neighbor (k-RNN) graph in the framework of manifold-ranking based retrieval. Among all tested feature point detectors and descriptors, Root-SIFT, the feature point ones, due to it is invariant to an array of image transforms, is the most reliable feature for calculating image similarity. The database consisting of images from scientific papers containing four popular benchmark test images served to test these methods.

show abstract

Fast and robust passive copy-move forgery detection using SURF and SIFT image features

Cited by 40 publications

References 19 publications

A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques

A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques

Técnica de Detección de Manipulación en Vídeos Digitales Basada en los Algoritmos de Compresión

Exploring Rotation and Scale Invariant Features in Image Pla- giarism Detection Using Manifold-Ranking Algorithm

Contact Info

Product

Resources

About