2-Levels of clustering strategy to detect and locate copy-move forgery in digital images

Faculty Computer Science Year: 2020
Type of Publication: ZU Hosted Pages:
Authors:
Journal: MULTIMEDIA TOOLS AND APPLICATIONS springer Volume:
Keywords : 2-Levels , clustering strategy , detect , locate copy-move    
Abstract:
Understanding is considered a key purpose of image forensic science in order to find out if a digital image is authenticated or not. It can be a sensitive task in case images are used as necessary proof as an impact judgment. it's known that There are several different manipulating attacks but, this copy move is considered as one of the most common and immediate one, in which a region is copied twice in order to give different information about the same scene, which can be considered as an issue of information integrity. The detection of this kind of manipulating has been recently handled using methods based on SIFT. SIFT characteristics are represented in the detection of image features and determining matched points. A clustering is a key step which always following SIFT matching in-order to classify similar matched points to clusters. The ability of the image forensic tool is represented in the assessment of the conversion that is applied between the two duplicated images of one region and located them correctly. Detecting copy-move forgery is not a new approach but using a new clustering approach which has been purposed by using the 2-level clustering strategy based on spatial and transformation domains and any previous information about the investigated image or the number of clusters need to be created is not necessary. Results from different data have been set, proving that the proposed method is able to individuate the altered areas, with high reliability and dealing with multiple cloning.
   
     
 
       

Author Related Publications

  • Ibrahiem Mahmoud Mohamed Elhenawy, "BERT-CNN: A Deep Learning Model for Detecting Emotions from Text", Tech Science Press, 2021 More
  • Ibrahiem Mahmoud Mohamed Elhenawy, "Determining Extractive Summary for a Single Document Based on Collaborative Filtering Frequency Prediction and Mean Shift Clustering", International Association of Engineers, 2019 More
  • Ibrahiem Mahmoud Mohamed Elhenawy, "A Review on the Applications of Neutrosophic Sets", Source: Journal of Computational and Theoretical Nanoscience, Volume 13, Number 1, January 2016, pp. 936-944(9), 2016 More
  • Ibrahiem Mahmoud Mohamed Elhenawy, "Feature and Intensity Based Medical Image Registration Using Particle Swarm Optimization", Springer, 2017 More
  • Ibrahiem Mahmoud Mohamed Elhenawy, "Solving 0–1 knapsack problem by binary flower pollination algorithm", Springer, 2018 More

Department Related Publications

  • Mohammed Abdel Basset Metwally Attia, "Discrete greedy flower pollination algorithm for spherical traveling salesman problem", Springer, 2019 More
  • Mohammed Abdel Basset Metwally Attia, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", Natural Sciences Publishing Cor., 2014 More
  • Saber Mohamed, "Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization", ELSEVEIR, 2015 More
  • Saber Mohamed, "An Improved Self-Adaptive Differential Evolution Algorithm for Optimization Problems", IEEE, 2013 More
  • Saber Mohamed, "Differential Evolution with Dynamic Parameters Selection for Optimization Problems", IEEE, 2014 More
Tweet