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.

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.

A REVIEW OF FINGERPRINT IMAGE ENHANCEMENT METHODS

2003 ◽  
Vol 03 (03) ◽  
pp. 401-424 ◽  
Author(s):  
HEIKKI AILISTO ◽  
MIKKO LINDHOLM ◽  
PAULI TIKKANEN
Keyword(s):  
Feature Extraction ◽  
Image Enhancement ◽  
Scientific Literature ◽  
Fourier Domain ◽  
Global Features ◽  
Fingerprint Verification ◽  
Fingerprint Image ◽  
Improve Image Quality ◽  
Alternative Approaches ◽  
Fingerprint Image Enhancement

Automatic fingerprint identification methods have become the most widely used technology in rapidly growing bioidentification applications. In this paper, different image enhancement approaches presented in the scientific literature are reviewed. Fingerprint verification can be divided into image acquisition, enhancement, feature extraction and matching steps. The enhancement step is needed to improve image quality prior to feature extraction. By far the most common approach relies on the filtering of the fingerprint images with filters adapted to local ridge orientation, but alternative approaches based on Fourier domain processing, direct ridge following and global features also exist. Methods of comparing the performance of enhancement methods are discussed. An example of the performance of different methods is given. Conclusions are made regarding the importance of effective enhancement, especially for noisy or low quality images.

Analysis of color Image Enhancement Using DWT, Wavelet Shrinkageand FHE Methods

2017 ◽  
Vol 7 (8) ◽  
pp. 56
Author(s):  
Ashish Dwivedi ◽  
Nirupma Tiwari
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Human Perception ◽  
Histogram Equalization ◽  
Wavelet Shrinkage ◽  
Visual Appearance ◽  
Enhancement Method ◽  
Fuzzy Histogram ◽  
Rgb Image

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.

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