2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE) 2021
DOI: 10.1109/icscee50312.2021.9497996
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Adaptive Latent Fingerprint Image Segmentation and Matching using Chan-Vese Technique Based on EDTV Model

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Cited by 15 publications
(2 citation statements)
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“…There are different scenarios to acquire contact-based fingerprints using various sensors. While the imaging techniques are advancing with sensor variations, the output of the fingerprint sensors are classified as (i) rolled full prints covering nail-to-nail area [11,12]; (ii) plain fingerprints covering flat regions [11,13]; (iii) live-scan swipe or partial fingerprints captured from portable devices [12,14]; and (iv) latent prints captured from crime scene surfaces [13,[15][16][17][18][19][20]. Each acquisition mode can have different physical finger placement with the sensor surface and therefore exhibits various challenges which call for alternatives.…”
Section: Image Acquisitionmentioning
confidence: 99%
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“…There are different scenarios to acquire contact-based fingerprints using various sensors. While the imaging techniques are advancing with sensor variations, the output of the fingerprint sensors are classified as (i) rolled full prints covering nail-to-nail area [11,12]; (ii) plain fingerprints covering flat regions [11,13]; (iii) live-scan swipe or partial fingerprints captured from portable devices [12,14]; and (iv) latent prints captured from crime scene surfaces [13,[15][16][17][18][19][20]. Each acquisition mode can have different physical finger placement with the sensor surface and therefore exhibits various challenges which call for alternatives.…”
Section: Image Acquisitionmentioning
confidence: 99%
“…Contact-based fingerprint scanning systems occupy the larger portion of the state-of-the-art fingerprint recognition in civilian applications, while the contactless domain become attractive due to the presence of portable, compact and high-resolution cameras with different image capture strategies such as multispectral, multiview and 3D-image capture. While the imaging techniques are advancing with sensor variations, the input fingerprint images are categorized as: (i) rolled full prints, by covering the nail-to-nail region of the finger (low resolution) [11,12]; (ii) plain prints, by covering flat region of the finger [11,13]; (iii) partial prints, captured from portable devices (high resolution) [12,14]; (iv) latent prints, acquired from touch surfaces (high resolution) [13,[15][16][17][18][19][20]; (v) multispectral [21]; and (vi) contactless (2D and 3D) images [3]. Figure 1 shows variations between such conventional contact-based and contactless fingerprints.…”
Section: Introductionmentioning
confidence: 99%