CNN based image resizing forensics for double compressed JPEG images

Billa, Nikhil Reddy; Das, Bibhash Pran; Biswal, Mrutyunjay; Okade, Manish

doi:10.1016/j.jisa.2023.103693

Journal of Information Security and Applications

2024

DOI: 10.1016/j.jisa.2023.103693

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CNN based image resizing forensics for double compressed JPEG images

Nikhil Reddy Billa,

Bibhash Pran Das,

Mrutyunjay Biswal

et al.

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2024

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Cited by 2 publications

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Robust primary quantization step estimation on resized and double JPEG compressed images

Zhang,

Chen,

Niu

et al. 2024

Multimed Tools Appl

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Robust primary quantization step estimation on resized and double JPEG compressed images

Zhang,

Chen,

Niu

et al. 2024

Multimed Tools Appl

View full text Add to dashboard Cite

Evaluation of Interoperability of CNN Models between MATLAB and Python Environments Using ONNX Runtime Model

Nagata,

Sakata,

Abe

et al. 2024

ACRT

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Recently, machine learning models such as CNNs (Convolutional Neural Networks) are implemented on various frameworks, such as PyTorch, TensorFlow, MATLAB, and others. However, it is not easy to ensure interoperability of a CNN model while maintaining complete equivalence on different frameworks. We developed a MATLAB application to efficiently design, train, and test prediction models for various kinds of defect detection tasks in CNN, SVM (Support Vector Machine), CAE (Convolutional Autoencoder), FCN (Fully Convolutional Network), VAE (Variational Autoencoder), YOLO (You Only Look Once), and FCDD (Fully Convolutional Data Description). In this study, a VGG19-based transfer learning CNN model built on MATLAB was exported to an ONNX (Open Neural Network eXchange) model and applied to a picking robot running on Python to detect defects. Two user interfaces for MATLAB and Python were developed to ensure pixel-level equivalence and ascertain interoperability on both frameworks. Experimental data show that the achievement of equivalence is dependent on the method used to interpolate images for downsizing. The validity and effectiveness are shown through classification experiments by an ONNX model and a peg-in-hole task by a small-sized industrial robot incorporated with the ONNX model.

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CNN based image resizing forensics for double compressed JPEG images

Cited by 2 publications

References 24 publications

Robust primary quantization step estimation on resized and double JPEG compressed images

Robust primary quantization step estimation on resized and double JPEG compressed images

Evaluation of Interoperability of CNN Models between MATLAB and Python Environments Using ONNX Runtime Model

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