Filter Design for Image Decomposition and Applications to Forensics

Robin Richter (), Duy H. Thai (), Carsten Gottschlich () and Stephan F. Huckemann ()
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Robin Richter: University of Göttingen, Felix-Bernstein-Institute for Mathematical Statistics in the Biosciences
Duy H. Thai: Colorado State University, Department of Mathematics
Carsten Gottschlich: University of Göttingen, Institute for Mathematical Stochastics
Stephan F. Huckemann: University of Göttingen, Felix-Bernstein-Institute for Mathematical Statistics in the Biosciences

Chapter 32 in Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 2023, pp 1155-1182 from Springer

Abstract: Abstract Employing image filters in image processing applications, essentially matrix convolution operators, has been an active field of research since a long time, and it is so very much still today. In the first part, we give a brief overview of imaging methods with emphasis on applications in fingerprint recognition and shoeprint forensics. In the second part, we propose a generalized discrete scheme for image decomposition that encompasses many of the existing methods. Due to its generality, it has the potential to learn, for specific use cases, a highly flexible set of imaging filters that are related to one another by rather general conditions.

Keywords: Image decomposition; Variational methods; Texture; Forensics; Fingerprint recognition (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-030-98661-2_92

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