A method for fingerprint image identification based on Gabor filter and power spectrum

2010 ◽  
Vol 20 (2) ◽  
pp. 201-209 ◽  
Author(s):  
S. L. de O. Gonzaga
Keyword(s):  
Power Spectrum ◽  
Gabor Filter ◽  
Fingerprint Image ◽  
Image Identification

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.

Analysis of Fingerprint Image Enhancement using Gabor Filtering with Different Orientation Field Values

2017 ◽  
Vol 5 (2) ◽  
pp. 427
Author(s):  
Pakutharivu P ◽  
Srinath M. V
Keyword(s):  
Image Enhancement ◽  
Gabor Filter ◽  
Orientation Angle ◽  
Input Image ◽  
False Identification ◽  
Gabor Filtering ◽  
Orientation Field ◽  
Fingerprint Image ◽  
Frequency Components ◽  
Fingerprint Image Enhancement

<p>Fingerprint image enhancement is the key process in IAFIS systems.  In order to reduce false identification ratio and to supply good fingerprint images to IAFIS systems for exact identification, fingerprint images are generally enhanced.  A filtering process tries to filter out the noise from the input image, and emphasize on low, high and directional spatial frequency components of an image.  This paper presents an experimental summary of enhancing fingerprint images using Gabor filters.  Frequency, width and window domain filter ranges are fixed. The orientation angle alone is modified by 0 radians, ,   and  radians. The experimental results show that Gabor filter enhances the fingerprint image in a better way than other filtering methods and extracts features. </p>

Preprocessing and Feature Extraction, Coding, Matching Algorithm for Fingerprint Image

2013 ◽  
Vol 805-806 ◽  
pp. 1900-1906
Author(s):  
He Ping Jia
Keyword(s):  
Feature Extraction ◽  
Gabor Filter ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Fingerprint Image ◽  
Development Platform ◽  
Traditional Algorithm ◽  
Fingerprint Image Enhancement ◽  
Global And Local

A set of fingerprint recognition algorithm was achieved mainly including Gamma controller normalization and equalizing, fingerprint image division, fingerprint image binarization and different direction Gabor filter for feature extraction; especially Fingerprint image enhancement and the textures based on Gabor filter, taking account of both global and local features of the fingerprints.using matlab 7.0 for development platform was verified,The experimental results showed the proposed algorithm can avoid all sorts of false characters more effectively and recognition rate is higher than traditional algorithm in the same conditions.

FINGERPRINT ENHANCEMENT USING WAVELET TRANSFORM COMBINED WITH GABOR FILTER

2004 ◽  
Vol 18 (08) ◽  
pp. 1391-1406 ◽  
Author(s):  
WEIPENG ZHANG ◽  
YUAN YAN TANG ◽  
XINGE YOU
Keyword(s):  
Wavelet Transform ◽  
Gabor Filter ◽  
Wavelet Coefficient ◽  
Input Image ◽  
Identification System ◽  
Gabor Filtering ◽  
Fingerprint Image ◽  
Fingerprint Enhancement ◽  
Novel Approach

The performance of automatic fingerprint identification system (AFIS) is heavily determined by the quality of the input image, thus an effective method to enhance the fingerprint image is essential in such a system. In this paper, we combine the filter-based method, which is mostly used nowadays with wavelet transform to achieve a more reliable and effective approach to fingerprint enhancement. This novel approach consists of five main steps, namely: (1) normalization, (2) decomposition, (3) wavelet coefficient adjustment, (4) Gabor filtering, and (5) reconstruction. Using this new method, a more clear fingerprint image can be obtained, which can distinctly improve the accuracy of the minutiae extraction module and finally achieve a better performance of the entire system. Experiments have been conducted in our study and positive experimental results have been received, which show that the proposed combined method is more effective and robust than other existing methods such as the filter-based and direct gray-level approaches.

scholarly journals Minutea Object Extraction in Fingerprint Image Using Morphological Methods and Gabor Filters

KOMTEKINFO ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 32-40
Author(s):  
Julius Santony
Keyword(s):  
Edge Detection ◽  
Object Detection ◽  
Gabor Filter ◽  
Extraction Process ◽  
Gabor Filters ◽  
Object Extraction ◽  
Original Image ◽  
Fingerprint Image ◽  
Minutiae Extraction

Minutiae is part of the fingerprint, which is the point where the fingerprint line stops or branches, which can be observed by scanning at a resolution of 500 pp. a fingerprint has minutiae that range from 50-100 pieces scattered throughout the surface of the fingerprint. To clarify the fingerprint can be done by extracting the minutiae contained in the fingerprint. With this extraction process, fingerprint images can be clarified, so identification of a fingerprint will be easy to do. This research extracts minutiae objects in the fingerprint image, so that the fingerprint line object can be seen clearly. The first stage in this research is object detection and edge detection using morphological methods. The next step is the extraction of minutiae objects with the gabor filter and minutiae extraction . The results obtained can display the fingerprint line of the fingerprint image clearly. From the results of testing 10 fingerprint images proved that the minutiae object in the image can be extracted, so that the fingerprint line of the image is clearer than the original image

scholarly journals A Novel Approach to Address Sensor Interoperability Using Gabor Filter

2017 ◽  
Vol 10 (2) ◽  
pp. 446-453
Author(s):  
Neha Bhatia ◽  
Himani Himani ◽  
Chander Kant
Keyword(s):  
Reliable Method ◽  
Gabor Filter ◽  
Gabor Filters ◽  
Poor Quality ◽  
Significant Loss ◽  
Biometric Authentication ◽  
Biometric System ◽  
Fingerprint Image ◽  
Novel Approach ◽  
Fingerprint Image Enhancement

Biometric authentication using fingerprint is one of the unique and reliable method of verification processes. Biometric System suffers a significant loss of performance when the sensor is changed during enrollment and authentication process. In this paper fingerprint sensor interoperability problem is addressed using Gabor filter and classifying images into good and poor quality. Gabor filters play an important role in many application areas for the enhancement of various types of fingerprint images. Gabor filters can remove noise, preserve the real ridges and valley structures, and it is used for fingerprint image enhancement. Experimental results on the FVC2004 databases show improvements of this approach.

Sign in / Sign up

Export Citation Format

Share Document