Results 81 to 90 of about 5,751 (196)

Fake Fingerprint Classification Using Hybrid Features Learning With Gradient Boosting

Applied Computational Intelligence and Soft Computing, Volume 2025, Issue 1, 2025.
Biometric security systems must be able to detect phony fingerprints to provide reliable authentication. The findings of this study suggest a hybrid approach to the detection of fake fingerprints that uses information on the texture and shape of the fingerprint.
Muhammad Salman Ali, Arslan Akram, Javed Rashid, Muhammad Arfan Jaffar, Dilawar Shah, Shujaat Ali, Muhammad Tahir, Ridha Ejbali   +7 more
wiley   +1 more source

FUSION OF WAVELET AND CURVELET COEFFICIENTS FOR GRAY TEXTURE CLASSIFICATION [PDF]

ICTACT Journal on Image and Video Processing, 2014
This study presents a framework for gray texture classification based on the fusion of wavelet and curvelet features. The two main frequency domain transformations Discrete Wavelet Transform (DWT) and Discrete Curvelet Transform (DCT) are analyzed.
M. Santhanalakshmi, K. Nirmala
doaj  

Classification of Mammography Images Based on Multifractal Analysis of BIMFs

International Journal of Biomedical Imaging, Volume 2025, Issue 1, 2025.
Breast cancer is a real public health problem. Several women with this disease have died from it. Breast cancer is one of the deadliest cancers. Currently, the only way to combat this scourge is the early detection of breast masses. Mammography is a breast x‐ray that allows images of the inside of the breast to be obtained using x‐rays, thereby ...
Fatima Ghazi, Khalil Ibrahimi, Fouad Ayoub, Aziza Benkuider, Mohamed Zraidi, Shashank Kaushik   +5 more
wiley   +1 more source

Blind Curvelet based Denoising of Seismic Surveys in Coherent and Incoherent Noise Environments

, 2018
The localized nature of curvelet functions, together with their frequency and dip characteristics, makes the curvelet transform an excellent choice for processing seismic data.
AlRegib, Ghassan, Deriche, Mohamed, Iqbal, Naveed   +2 more
core  

Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients [PDF]

, 2008
We address the denoising of images contaminated with multiplicative noise, e.g. speckle noise. Classical ways to solve such problems are filtering, statistical (Bayesian) methods, variational methods, and methods that convert the multiplicative noise ...
Durand, Sylvain, Fadili, Jalal, Nikolova, Mila   +2 more
core   +5 more sources

Artificial Intelligence in Melanoma Detection: A Review of Current Technologies and Future Directions

International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.
Early and accurate identification of malignant melanoma continues to be a major challenge for clinicians in the field. Traditional diagnostic approaches, including physical examination, histology, imaging, and nodal assessments, are frequently costly, require significant expertise, and can display large variations among clinicians.
Fakhre Alam, Asad Ullah, Dilawar Shah, Shujaat Ali, Muhammad Tahir, Yingjie Yang   +5 more
wiley   +1 more source

Denoising of CT and MRI Images Using Decomposition-Based Curvelet Thresholding and Classical Filtering Techniques

Applied Sciences
Medical image denoising is crucial for enhancing the diagnostic accuracy of CT and MRI images. This paper presents a modular hybrid framework that combines multiscale decomposition techniques (Empirical Mode Decomposition, Variational Mode Decomposition,
Mahmoud Nasr, Krzysztof Brzostowski, Rafał Obuchowicz, Adam Piórkowski   +3 more
doaj   +1 more source

Leveraging High‐Dimensional Mapping for Effective JPEG Steganalysis

International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.
Steganography is a critical information‐hiding technique widely used for the covert transmission of secret information on social media. In contrast, steganalysis plays a key role in ensuring information security. Although various effective steganalysis algorithms have been proposed, existing studies typically treat color images as three independent ...
Meng Xu, Xiangyang Luo, Beijing Chen
wiley   +1 more source

Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble

BMC Bioinformatics, 2011
Background Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture thousands of images from massively parallel experiments such as RNA ...
Pham Tuan D, Zhang Bailing
doaj   +1 more source

Sparse seismic imaging using variable projection

, 2012
We consider an important class of signal processing problems where the signal of interest is known to be sparse, and can be recovered from data given auxiliary information about how the data was generated.
Aravkin, Aleksandr Y., Tu, Ning, van Leeuwen, Tristan   +2 more
core   +1 more source