Performance Analysis of Fingerprint Based Image Enhancement and Minutiae Extraction

2018 ◽  
Vol 8 (5) ◽  
pp. 43
Author(s):  
Rajneesh Jain ◽  
Sheelesh Kr. Sharma ◽  
Pankaj Agrawal
Keyword(s):  
Performance Analysis ◽  
Image Enhancement ◽  
Histogram Equalization ◽  
Fingerprint Identification ◽  
Fingerprint Image ◽  
Minutiae Extraction ◽  
Fingerprint Pattern ◽  
Fingerprint Image Enhancement

Extracting minutiae from fingerprint images is one of the most important steps in automatic fingerprint identification and classification. Minutiae are local discontinuities in the fingerprint pattern, mainly terminations and bifurcations. In this work we have propose a method for fingerprint image enhancement. Using histogram equalization over filtering and then minutia are calculated. The   results   achieved   are compared   with   those   obtained   through   some   other methods.  The Results show some improvement in the minutiae extraction in terms of quantity.

scholarly journals New Combined Technique for Fingerprint Image Enhancement

2016 ◽  
Vol 11 (1) ◽  
pp. 222 ◽  
Author(s):  
Alaa Ahmed Abbood ◽  
Mohammed Sabbih Hamoud Al-Tamimi ◽  
Sabine U. Peters ◽  
Ghazali Sulong
Keyword(s):  
Image Enhancement ◽  
Histogram Equalization ◽  
Fingerprint Image ◽  
Pixel Intensity ◽  
Improve Image Quality ◽  
Enhancement Method ◽  
Equalization Technique ◽  
Fingerprint Image Enhancement ◽  
Normalization Process ◽  
Combined Technique

This paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furthermore, the Binarization and Skeletonization techniques were implemented to differentiate between the ridge and valley structures and to obtain one pixel-wide lines. Finally, the Fusion technique was used to merge the results of the Histogram Equalization process with the Skeletonization process to obtain the new high contrast images. The proposed method was tested in different quality images from National Institute of Standard and Technology (NIST) special database 14. The experimental results are very encouraging and the current enhancement method appeared to be effective by improving different quality images.

FINGERPRINT IMAGE ENHANCEMENT USING MEDIAN SIGMOID FILTER

2015 ◽  
Vol 75 (4) ◽  
Author(s):  
Ainul Azura Abdul Hamid ◽  
Rosely Kumoi ◽  
Mohd Shafry Mohd Rahim ◽  
Nur Zuraifah Syazrah
Keyword(s):  
Image Enhancement ◽  
New Combination ◽  
Noisy Image ◽  
Fingerprint Image ◽  
Acquisition Process ◽  
Minutiae Extraction ◽  
Fingerprint Image Enhancement

Quality of fingerprint image is most essential to ensure good performance of minutiae extraction result since it depends heavily on the quality of fingerprint images. Fingerprint image with noise usually will produce spurious minutiae. In this paper, new combination filter called Median Sigmoid (MS) filter is introduced to remove the unwanted noise created during the acquisition process and hence increasing the accuracy of minutiae extraction result. The result shows that MS filter is an effective filter in enhancing the quality of a noisy image.

FINGERPRINT IMAGE ENHANCEMENT USING CNN FILTERING TECHNIQUES

2003 ◽  
Vol 13 (06) ◽  
pp. 453-460 ◽  
Author(s):  
ERTUGRUL SAATCI ◽  
VEDAT TAVSANOGLU
Keyword(s):  
Image Enhancement ◽  
Fingerprint Recognition ◽  
Fingerprint Image ◽  
Directional Filter ◽  
Ridge Pattern ◽  
Fingerprint Pattern ◽  
Fingerprint Image Enhancement ◽  
Filtering Techniques

Due to noisy acquisition devices and variation in impression conditions, the ridgelines of fingerprint images are mostly corrupted by various kinds of noise causing cracks, scratches and bridges in the ridges as well as blurs. These cause matching errors in fingerprint recognition. For an effective recognition the correct ridge pattern is essential which requires the enhancement of fingerprint images. Segment by segment analysis of the fingerprint pattern yields various ridge direction and frequencies. By selecting a directional filter with correct filter parameters to match ridge features at each point, we can effectively enhance fingerprint ridges. This paper proposes a fingerprint image enhancement based on CNN Gabor-Type filters.

scholarly journals Fingerprint Image Enhancement By Develop Mehtre Technique

2011 ◽  
Vol 2 (6) ◽  
pp. 171-182 ◽  
Author(s):  
Mustafa Salah Khalefa ◽  
Zaid Amin Abduljabar ◽  
Huda Ameer Zeki
Keyword(s):  
Image Enhancement ◽  
Fingerprint Image ◽  
Fingerprint Image Enhancement
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