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Improving the Accuracy in Copy-Move Image Detection: A Model of Sharpness and Blurriness

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Abstract

The paper suggests a model based on the sharpness and blurriness to confirm the exact tampered areas from the suspicious ones which are detected from similar regions. In copy-move image detection, most research focus on comparing and finding areas with similar properties on the image. Actually, the same areas are not certainly done by copy-move manipulation, they may be the image texture. A model from the sharpness at the collage borderlines and the blurriness inside the image area is built to determine if the areas are really caused by the copy-move manipulation. The combination of feature extraction using oriented FAST and rotated BRIEF (ORB) and tampered region confirmation using a logistic regression model with 98% on accuracy proves the efficiency of the proposed methods.

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Funding

This study was funded by the International University, a research project with Grant number SV2020-IT-02/HĐ-KHCN.

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Authors and Affiliations

  1. International University, Ho Chi Minh City, Vietnam

    Kha-Tu Huynh, Tu-Nga Ly & Phuong-Thanh Nguyen

  2. Vietnam National University, Ho Chi Minh City, Vietnam

    Kha-Tu Huynh, Tu-Nga Ly & Phuong-Thanh Nguyen

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  1. Kha-Tu Huynh
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  2. Tu-Nga Ly
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  3. Phuong-Thanh Nguyen
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Correspondence to Kha-Tu Huynh.

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This article is part of the topical collection “Future Data and Security Engineering 2020” guest-edited by Tran Khanh Dang.

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Huynh, KT., Ly, TN. & Nguyen, PT. Improving the Accuracy in Copy-Move Image Detection: A Model of Sharpness and Blurriness. SN COMPUT. SCI. 2, 278 (2021). https://doi.org/10.1007/s42979-021-00682-w

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