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This thesis explores the use of Curvelet transform techniques for biometric person identification, particularly focusing on palmprint recognition and fusion with facial recognition. The work highlights the advantages of using Curvelet transforms for better feature extraction, leading to improved identification accuracy in both uni-modal and bi-modal biometric systems. Experiments conducted on multiple datasets demonstrate the efficacy of the proposed methods, especially in terms of...

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What is curvelet transform-based techniques for?

Curvelet transform-based techniques are used for efficiently analyzing and processing multidimensional data, especially for image processing tasks like edge detection and denoising.

Who is required to file curvelet transform-based techniques for?

There is no specific requirement to file curvelet transform-based techniques as they are mathematical and computational methods used primarily in scientific research and engineering applications.

How to fill out curvelet transform-based techniques for?

Filling out curvelet transform-based techniques typically involves implementing algorithms in programming languages such as MATLAB or Python, utilizing libraries that support curvelet transformations.

What is the purpose of curvelet transform-based techniques for?

The purpose of curvelet transform-based techniques is to provide a better representation of images and signals by capturing their edges and curves more effectively than traditional methods like Fourier transform.

What information must be reported on curvelet transform-based techniques for?

Typically, reports using curvelet transform-based techniques would include details on the algorithms used, parameters for the transform, and results obtained from processing the data.

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