A Review of Digital Latent Fingerprint Image Processing with a Special Focus on Techniques for Separation of Overlapped Fingerprint Images

2019 ◽  
pp. 287-299
Author(s):  
Poornima Eshwar Raj Gundgurti ◽  
Prakash Pattan ◽  
Padmavati Gundgurti
Keyword(s):  
Image Processing ◽  
Special Focus ◽  
Fingerprint Image ◽  
Latent Fingerprint

Application of Fingerprint-Matching Algorithm in Smart Gun Using Touch-Less Fingerprint Recognition System

2020 ◽  
pp. 122-128
Author(s):  
Saifullah Khalid
Keyword(s):  
Recognition System ◽  
Fingerprint Recognition ◽  
Fingerprint Matching ◽  
Fingerprint Image ◽  
Matching Algorithm ◽  
Latent Fingerprint ◽  
Recognition Systems

Fingerprint recognition systems are widely used in the field of biometrics. Many existing fingerprint sensors acquire fingerprint images as the user's fingerprint is contacted on a solid flat sensor. Because of this contact, input images from the same finger can be quite different and there are latent fingerprint issues that can lead to forgery and hygienic problems. For these reasons, a touchless fingerprint recognition system has been investigated, in which a fingerprint image can be captured without contact. While this system can solve the problems which arise through contact of the user's finger, other challenges emerge.

Fingerprint Preprocessing and Recognition System Development and Design

2014 ◽  
Vol 971-973 ◽  
pp. 1897-1900
Author(s):  
Qian Wu
Keyword(s):  
Image Processing ◽  
System Development ◽  
Recognition System ◽  
Identity Authentication ◽  
Fingerprint Identification ◽  
Fingerprint Image ◽  
Image Preprocessing ◽  
The Core ◽  
Core Technology ◽  
Theoretical Significance

fingerprint image preprocessing and is one of the branch of image processing and pattern recognition, after several years of development the increasing maturity of the technology. Due to the uniqueness and invariability of fingerprints, and the feasibility and practicability of the fingerprint identification technology, fingerprint identification has become the most popular, the most convenient, one of the most reliable personal identity authentication technology. Although on this technology has a variety of molding products, but because many of the core technology by commercial interests and confidentiality need without open, as well as the development of the society put forward higher requirements on the performance of the system, so in this field of research, still has important theoretical significance and practical value.

Multi-Template Processing of Fingerprint Recognition Algorithm

2014 ◽  
Vol 610 ◽  
pp. 332-338
Author(s):  
Lian Ying Zou ◽  
Ying Zhou ◽  
Xiang Dong ◽  
Yu Chen
Keyword(s):  
Image Processing ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Fingerprint Image ◽  
Ridge Line ◽  
Black And White ◽  
White Point ◽  
Direction Filter ◽  
Fingerprint Feature ◽  
Line Texture

Using multi-template processing algorithm, the fingerprint features are accurately collected. Through normalization, make the black and white point contrast of the fingerprint image more obviously, strengthen the ridge line texture. Direction calculating algorithm is based on the grey value of the neighborhood pixels. It can be implemented simply and speedily. Through direction filter, noises can be removed, and the contrast of the fingerprint’s ridge lines and valley lines can be enhanced. After binary converting, all information of the fingerprint is stored with 0 and 1. The effect of thinning is to make the fingerprint image more distinct to extract the fingerprint feature point easily. These steps had been implemented on Altera DE2 board with HDL codes. The experimental results indicate that the multi-template algorithm of fingerprint image processing is correct and practicable.

scholarly journals PENCOCOKAN GAMBAR SIDIK JARI DENGAN KAMERA HANDPHONE MENGGUNAKAN METODE RANSAC DAN TRANSFORMASI AFFINE BERBASIS ANDROID

Compiler ◽  
2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Haruno Sajati ◽  
Dwi Nughraheny ◽  
Nova Adi Suwarso
Keyword(s):  
Image Processing ◽  
Gabor Filter ◽  
Histogram Equalization ◽  
Fingerprint Recognition ◽  
Android Application ◽  
Fingerprint Image ◽  
Android Os ◽  
Support Tools ◽  
Fingerprint Pattern ◽  
Fingerprint Sensor

Fingerprints occur due to stroke differences. These stroke differences have occurred at a time when humans are still fetal form. A normal fingerprint pattern is formed of lines and spaces. These lines are called ridges whereas the spaces between these lines are called valleys. To make an introduction to the fingerprint image requires a variety of support tools. Starting from a fingerprint machine, a smartphone that has a fingerprint sensor and much more. In this research, the acquisition of image is done by grayscaling, histogram equalization, gabor filter, binary, thinning, 8 neighbors, matching.The result of making android application with the method that has been described to show unfavorable results seen from the calculation of the accuracy of 63%. Based on testing the specs android OS devices, this application can run on android with OS 4.4.2 specification kitkat.Fingerprints occur due to stroke differences. These stroke differences have occurred at a time when humans are still fetal form. A normal fingerprint pattern is formed of lines and spaces. These lines are called ridges whereas the spaces between these lines are called valleys. To make an introduction to the fingerprint image requires a variety of support tools. Starting from a fingerprint machine, a smartphone that has a fingerprint sensor and much more. In this research, the acquisition of image is done by grayscaling, histogram equalization, gabor filter, binary, thinning, 8 neighbors, matching.The result of making android application with the method that has been described to show unfavorable results seen from the calculation of the accuracy of 63%. Based on testing the specs android OS devices, this application can run on android with OS 4.4.2 specification kitkat. Keywords : OCR Fingerprint, Fingerprint recognition, Minutiae based matching, Fingerprint image processing.

Adaptive Latent Fingerprint Image Segmentation and Matching using Chan-Vese Technique Based on EDTV Model

2021 ◽  
Author(s):  
Shadi M S Hilles ◽  
Abdilahi Liban ◽  
Abdullah Mahmoud Altrad ◽  
Othman A. M. Miaikil ◽  
Yousef A. Baker El-Ebiary ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Fingerprint Image ◽  
Latent Fingerprint
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