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@article{148295,
        author = {Harikrishnan K A and Anila raj and Athira rajan and Sandhyamol s and Akhija Lakshmi R},
        title = {Super resolution for fingerprint recognition},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {6},
        number = {1},
        pages = {168-171},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=148295},
        abstract = {Super-resolution (SR) technique reconstructs a higher-resolution image. For more than three decades SR has been developed, both multi-frame and single-frame SR have significant applications in our daily life.Finger print recognition system is used as an application of super resolution in forensic department. Latent fingerprints have been used as an important evidence to identify criminals in law enforcement agencies for more than a century.Prior to feature extraction, fingerprint enhancement is necessary to remove noises and enhance the clarity of ridge structures in latent fingerprints. First, the total variation model is applied to decompose   into cartoon and texture components. The cartoon component with most of the nonfingerprint patterns is removed as the structured noise, whereas the texture component consisting of the weak latent fingerprint is enhanced in the next stage..A multiscale patch-based sparse representation method is used for the enhancement of the texture component.  Gabor elementary functions  use dictionaries to  capture the characteristics of fingerprint ridge structure, and multiscale patch-based sparse representation is iteratively applied to reconstruct high-quality fingerprint image.},
        keywords = {Latent fingerprint enhancement, sparse representation},
        month = {},
        }