Semi-Fragile Image Watermarking Using Quantization-Based DCT for Tamper Localization

This paper proposes a tamper detection technique for semi-fragile watermarking using Quantization-based Discrete Cosine Transform (DCT) for tamper localization. In this study, the proposed embedding strategy is investigated by experimental tests over the diagonal order of the DCT coefficients. The cover image is divided into non-overlapping blocks of size 8 × 8 pixels. The DCT is applied to each block, and the coefficients are arranged using a zig-zag pattern within the block. In this study, the low-frequency coefficients are selected to examine the impact of the imperceptibility score and tamper detection accuracy. High accuracy of tamper detection can be achieved by checking the surrounding blocks to determine whether the corresponding block has been tampered with. The proposed tamper detection is tested under various malicious, incidental, and hybrid attacks (both incidental and malicious attacks). The experimental results demonstrate that the proposed technique achieves a Peak-Signal-to-Noise Ratio (PSNR) value of 41.2318 dB, an average Structural Similarity Index Measure (SSIM) value of 0.9768. The proposed scheme is also evaluated against malicious attacks such as copy-move, object deletion, object manipulation, and collage attacks. The proposed scheme can detect the malicious attack localization under various tampering rates. In addition, the proposed scheme can still detect tampered pixels under a hybrid attack, such as a combination of malicious and incidental attacks, with an average accuracy of 96.44%.

Publication Details

Journal
Computers, materials & continua/Computers, materials & continua (Print)
Published
2025-11-10
DOI
https://doi.org/10.32604/cmc.2025.069229
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
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article

Semi-Fragile Image Watermarking Using Quantization-Based DCT for Tamper Localization

Computers, materials & continua/Computers, materials & continua (Print)
Advanced Steganography and Watermarking Techniques
article

Semi-Fragile Image Watermarking Using Quantization-Based DCT for Tamper Localization

article en

Abstract

This paper proposes a tamper detection technique for semi-fragile watermarking using Quantization-based Discrete Cosine Transform (DCT) for tamper localization. In this study, the proposed embedding strategy is investigated by experimental tests over the diagonal order of the DCT coefficients. The cover image is divided into non-overlapping blocks of size 8 × 8 pixels. The DCT is applied to each block, and the coefficients are arranged using a zig-zag pattern within the block. In this study, the low-frequency coefficients are selected to examine the impact of the imperceptibility score and tamper detection accuracy. High accuracy of tamper detection can be achieved by checking the surrounding blocks to determine whether the corresponding block has been tampered with. The proposed tamper detection is tested under various malicious, incidental, and hybrid attacks (both incidental and malicious attacks). The experimental results demonstrate that the proposed technique achieves a Peak-Signal-to-Noise Ratio (PSNR) value of 41.2318 dB, an average Structural Similarity Index Measure (SSIM) value of 0.9768. The proposed scheme is also evaluated against malicious attacks such as copy-move, object deletion, object manipulation, and collage attacks. The proposed scheme can detect the malicious attack localization under various tampering rates. In addition, the proposed scheme can still detect tampered pixels under a hybrid attack, such as a combination of malicious and incidental attacks, with an average accuracy of 96.44%.

Computers, materials & continua/Computers, materials & continua (Print)Vol. 86(2)
Openalex Percentile: Top 42%
Advanced Steganography and Watermarking Techniques
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Semi-Fragile Image Watermarking Using Quantization-Based DCT for Tamper Localization · Computers, materials & continua/Computers, materials & continua (Print) (2025) | TGRS Research Map | TGRS