Latent Fingerprint Enhancement Based on Orientation Guided Sparse Representation

Wei, Kaifeng; Liu, Manhua

doi:10.1007/978-3-319-46654-5_23

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…The cumulative match characteristics (CMC) curve result of proposed algorithm outperforms when compared with three other enhancement algorithms [9] [18] 14]. Further Wei and Liu [22] improves the improves the proposed algorithm by removing the structured noise using total variance decomposition model and reconstructing the low quality fingerprints using orientation based sparse representation.…”

Section: Enhancement Techniquesmentioning

confidence: 98%

“…Wei and Liu [22] Enhancement Total Variance decomposition Model and orientation guided sparse representation…”

Section: Nist Sd27mentioning

confidence: 99%

“…Average accuracy rate of 81.84% is achieved by proposed algorithm. Many researchers evaluated the system performance in terms of receiver operating characteristic (ROC) [14] and cumulative match characteristics (CMC) [15] [17] [21] [22] curves by comparing their proposed system with other existing systems using some open source fingerprint matching software e.g. VeriFinger SDK [16].…”

Section: How To Evaluate Different Fingerprint Enhancement Techniqmentioning

confidence: 99%

See 2 more Smart Citations

Filters to Dictionary based Enhancement Techniques for Latent Fingerprints Matchingc

Jindal¹

2018

IJRASET

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Latent fingerprints are the finger skin impressions in a groove and ridge pattern left when fingertips come in contact with any surface. In forensics investigation, latent fingerprints plays as principal evidence to identify and convict criminals. Due to the presence of overlapping noisy patterns and complex ridge structure, they are usually unclear and of poor quality. The discipline of latent fingerprint detection has gain attention of many researchers over the years and many advances have been made but it is still challenging to accomplish the task by offering a quick, reliable and accurate latent fingerprint detection system. The presence of spoiled minutiae information, ridge and overlapping patterns make the task more complicated. The latent fingerprints do not serve any purpose before the enhancement and reconstruction of the ridge patterns, minutiae information and their quality. Prior to latent fingerprint detection and feature extraction, latent fingerprint enhancement is absolutely requisite to improve the quality for accurate fingerprint detection. This paper presents an analysis of various latent fingerprint enhancement techniques by comparing the work of numerous researchers. The paper sheds some light on the issues and challenges in the process of latent fingerprint detection. In addition, the paper also presents various datasets available for latent fingerprint detection.

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Section: Enhancement Techniquesmentioning

confidence: 98%

“…Wei and Liu [22] Enhancement Total Variance decomposition Model and orientation guided sparse representation…”

Section: Nist Sd27mentioning

confidence: 99%