Agit Amrullah, Ferda Ernawan^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-16, 2026, DOI:10.32604/cmc.2025.069229 - 09 December 2025

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… More >

Muhammad Osama¹, Sarwar Shah Khan^2,*, Sajid Khan², Muzammil Khan³, Mian Muhammad Danyal⁴, Reshma Khan¹

Digital Engineering and Digital Twin, Vol.3, pp. 17-34, 2025, DOI:10.32604/dedt.2025.066344 - 19 August 2025

Abstract Image fusion is a technique used to combine essential information from two or more source images into a single, more informative output image. The resulting fused image contains more meaningful details than any individual source image. This study focuses on multi-focus image fusion, a crucial area in image processing. Due to the limited depth of field of optical lenses, it is often challenging to capture an image where all areas are in focus simultaneously. As a result, multi-focus image fusion plays a key role in integrating and extracting the necessary details from different focal regions.… More >

Fatima Abu Siryeh^*, Hussein Alrammahi, Abdullahi Abdu İbrahim

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5021-5046, 2025, DOI:10.32604/cmc.2025.065206 - 30 July 2025

Abstract Biometric template protection is essential for finger-based authentication systems, as template tampering and adversarial attacks threaten the security. This paper proposes a DCT-based fragile watermarking scheme incorporating AI-based tamper detection to improve the integrity and robustness of finger authentication. The system was tested against NIST SD4 and Anguli fingerprint datasets, wherein 10,000 watermarked fingerprints were employed for training. The designed approach recorded a tamper detection rate of 98.3%, performing 3–6% better than current DCT, SVD, and DWT-based watermarking approaches. The false positive rate (≤1.2%) and false negative rate (≤1.5%) were much lower compared to previous… More >

Abdullah Alenizi¹, Mohammad Sajid Mohammadi², Ahmad A. Al-Hajji², Arshiya Sajid Ansari^1,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2463-2494, 2024, DOI:10.32604/cmc.2024.051826 - 15 August 2024

Abstract Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item. From ancient times to the present, the security of secret or vital information has always been a significant problem. The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest. Therefore, several approaches, including steganography, have been developed by researchers over time to enable safe data transit. In this review, we have discussed image steganography based on Discrete Cosine Transform (DCT) algorithm, etc. We have also discussed image steganography based… More >

Shahid Naseem¹, Tariq Mahmood^2,3, Amjad Rehman Khan², Umer Farooq¹, Samra Nawazish⁴, Faten S. Alamri^5,*, Tanzila Saba²

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 801-817, 2024, DOI:10.32604/cmc.2024.047623 - 25 April 2024

Abstract Recently, there have been several uses for digital image processing. Image fusion has become a prominent application in the domain of imaging processing. To create one final image that proves more informative and helpful compared to the original input images, image fusion merges two or more initial images of the same item. Image fusion aims to produce, enhance, and transform significant elements of the source images into combined images for the sake of human visual perception. Image fusion is commonly employed for feature extraction in smart robots, clinical imaging, audiovisual camera integration, manufacturing process monitoring,… More >

Pengju Zhang¹, Jingbing Li^1,2,*, Uzair Aslam Bhatti^1,2, Jing Liu³, Yen-wei Chen⁴, Dekai Li¹, Lei Cao¹

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5853-5870, 2023, DOI:10.32604/cmc.2023.036462 - 29 April 2023

Abstract The amount of 3D data stored and transmitted in the Internet of Medical Things (IoMT) is increasing, making protecting these medical data increasingly prominent. However, there are relatively few researches on 3D data watermarking. Moreover, due to the particularity of medical data, strict data quality should be considered while protecting data security. To solve the problem, in the field of medical volume data, we proposed a robust watermarking algorithm based on Polar Cosine Transform and 3D-Discrete Cosine Transform (PCT and 3D-DCT). Each slice of the volume data was transformed by PCT to obtain feature row… More >

Mingshuai Sheng¹, Jingbing Li^1,2,*, Uzair Aslam Bhatti^1,2,3, Jing Liu⁴, Mengxing Huang^1,5, Yen-Wei Chen⁶

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 293-309, 2023, DOI:10.32604/cmc.2023.036438 - 06 February 2023

Abstract Medical images are used as a diagnostic tool, so protecting their confidentiality has long been a topic of study. From this, we propose a Resnet50-DCT-based zero watermarking algorithm for use with medical images. To begin, we use Resnet50, a pre-training network, to draw out the deep features of medical images. Then the deep features are transformed by DCT transform and the perceptual hash function is used to generate the feature vector. The original watermark is chaotic scrambled to get the encrypted watermark, and the watermark information is embedded into the original medical image by XOR… More >

M. Jamuna Rani^1,*, C. Vasanthanayaki²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1953-1970, 2023, DOI:10.32604/csse.2023.028713 - 03 November 2022

Abstract Underwater imagery and transmission possess numerous challenges like lower signal bandwidth, slower data transmission bit rates, Noise, underwater blue/green light haze etc. These factors distort the estimation of Region of Interest and are prime hurdles in deploying efficient compression techniques. Due to the presence of blue/green light in underwater imagery, shape adaptive or block-wise compression techniques faces failures as it becomes very difficult to estimate the compression levels/coefficients for a particular region. This method is proposed to efficiently deploy an Extreme Learning Machine (ELM) model-based shape adaptive Discrete Cosine Transformation (DCT) for underwater images. Underwater More >

Yu Fan^1,6, Jingbing Li^1,2,*, Uzair Aslam Bhatti^1,2, Chunyan Shao¹, Cheng Gong¹, Jieren Cheng^3,5, Yenwei Chen⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1279-1302, 2023, DOI:10.32604/cmc.2023.031445 - 22 September 2022

Abstract Medical images are a critical component of the diagnostic process for clinicians. Although the quality of medical photographs is essential to the accuracy of a physician’s diagnosis, they must be encrypted due to the characteristics of digital storage and information leakage associated with medical images. Traditional watermark embedding algorithm embeds the watermark information into the medical image, which reduces the quality of the medical image and affects the physicians’ judgment of patient diagnosis. In addition, watermarks in this method have weak robustness under high-intensity geometric attacks when the medical image is attacked and the watermarks… More >

Anil Kumar Yadav¹, R. K. Pateriya², Nirmal Kumar Gupta³, Punit Gupta^4,*, Dinesh Kumar Saini⁴, Mohammad Alahmadi⁵

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2697-2712, 2022, DOI:10.32604/cmc.2022.023052 - 29 March 2022

Abstract Face recognition systems have enhanced human-computer interactions in the last ten years. However, the literature reveals that current techniques used for identifying or verifying faces are not immune to limitations. Principal Component Analysis-Support Vector Machine (PCA-SVM) and Principal Component Analysis-Artificial Neural Network (PCA-ANN) are among the relatively recent and powerful face analysis techniques. Compared to PCA-ANN, PCA-SVM has demonstrated generalization capabilities in many tasks, including the ability to recognize objects with small or large data samples. Apart from requiring a minimal number of parameters in face detection, PCA-SVM minimizes generalization errors and avoids overfitting problems More >