Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India

Research Article

Image Features for Image Forgery Detection System in Digital Image Forensics

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  • @INPROCEEDINGS{10.4108/eai.27-2-2020.2303220,
        author={Hlaing Htake  Khaung Tin},
        title={Image Features for Image Forgery Detection System in Digital Image Forensics},
        proceedings={Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India},
        publisher={EAI},
        proceedings_a={ICIDSSD},
        year={2021},
        month={3},
        keywords={image features forgery detection image forensics image retrieval},
        doi={10.4108/eai.27-2-2020.2303220}
    }
    
  • Hlaing Htake Khaung Tin
    Year: 2021
    Image Features for Image Forgery Detection System in Digital Image Forensics
    ICIDSSD
    EAI
    DOI: 10.4108/eai.27-2-2020.2303220
Hlaing Htake Khaung Tin1,*
  • 1: Faculty of Information Science, University of Computer Studies, Hinthada, Myanmar
*Contact email: hlainghtakekhaungtin@gmail.com

Abstract

Digital image forensics is a term that is used in altered situations with slightly altered meanings. To change the meaning of an image or forensic Can be used in broadcasting to influence readers' opinions. The fake copy-move is an influence on the image; Some parts of the area are copied and copied to another district in the same area. This paper presents a study of several image features for feature extraction in digital image forensics and an investigation of many issues in image forgery detection. This paper took the exact same pixel values and presented an accurate study and evaluation of a digital image known as anesthesia for two imaging areas. A relative investigation of main methods for feature extraction is also given. Time complexity; Accuracy and detection methods based on false positives and false positives can be used to identify this type of false alarm.