Authentications of Myanmar National Registration Card

The automatic identification system of Myanmar national registration card (NRC) holder is presented in this paper. The proposed system can be handled the identification by the extracted low quality face image and fingerprint image from Myanmar NRC. Both of the facial recognition and fingerprint recognition system are developed for Myanmar citizenship confirmation. Age invariant face recognition algorithm is performed based on combination of DiaPCA (Diagonal principal Component Analysis) and KNN (Kth nearest neighbor classifier) approaches. An algorithm of the fingerprint recognition is proposed for recognition of the poor quality fingerprint image with fabric background.  Several experiments have been done for confirming the effectiveness of the proposed approach

Domain Fingerprints for No-reference Image Quality Assessment

Human fingerprints are detailed and nearly unique markers of human identity. Such a unique and stable fingerprint is also left on each acquired image. It can reveal how an image was degraded during the image acquisition procedure and thus is closely related to the quality of an image. In this work, we propose a new no-reference image quality assessment (NR-IQA) approach called domain-aware IQA (DA-IQA), which for the first time introduces the concept of domain fingerprint to the NR-IQA field. The domain fingerprint of an image is learned from image collections of different degradations and then used as the unique characteristics to identify the degradation sources and assess the quality of the image. To this end, we design a new domain-aware architecture, which enables simultaneous determination of both the distortion sources and the quality of an image. With the distortion in an image better characterized, the image quality can be more accurately assessed, as verified by extensive experiments, which show that the proposed DA-IQA performs better than almost all the compared state-of-the-art NR-IQA methods.Comment: accepted by IEEE Transactions on Circuits and Systems for Video Technology (TCSVT

Fingerprint scanning

Otisky prstů jsou nejstarší a nejpoužívanější metodou identifikace v biometrii. Kritickým krokem je spolehlivá extrakce markant z otisků prstů. Bohužel obrázky otisků nejsou vždy dokonale kvalitní, můžou být degradovány a poškozeny přirozenou variancí kůže a podmínkami snímání. Tudíž jsou nezbytné techniky vylepšovaní před extrakcí markant. Tato práce obsahuje implementaci tří technik vylepšování otisků, extrakci markant a konstrukci zařízení pro snímání otisků. Experimenty jsou provedeny se dvěma sadami otisků pro zhodnocení implementovaných technik.Fingerprints are the oldest and most used form of biometric identification. A critical step is reliable extract minutiae from the fingerprint images. However fingerprint images are rarely of perfect quality, they may be degraded and corrupted due to natural variations in skin and sensing conditions. Thus, image enhancement techniques are necessary prior to minutiae extraction. This work includes implementation of three techniques for fingerprint image enhancement, minutiae extraction and consturction of fingerprint reading device. Experiments are realized with two sets of fingerprints to evaluate the performance of implemented techniques.

Integration of median filter and oriented field estimation for fingerprint identification system

The Fingerprint Identification System (FIS) has been used and applied into various aspects. The system used identification based on fingerprint to give an authorization and identification to every person that wants to access the system. However, there are some research issues that affect the system accuracy such as noise element and low-quality fingerprint image. To solve this problem, this project will proposed two selection methods; which are Median filter to reduce noise element and Orientation Field Extimation method to enhance the low quality image. This proposed methods is implement in order to get an accurate result and high performance system. In order to verify the system identification, two experiments has been done which are functional test and accuracy test. This test will used 16 images from FVC2004DB1 set. From this test, there will be three results that being focus on which are the computational time, high peak value, False Rejection Rate (FRR), False Acceptance Rate (FAR) and Matching Rate. These values are used in order to verify high performance in the system, by comparing the proposed system with other existing system. By doing this experiment, it shown that by using the proposed methods it has lower value in average time and FRR value; which is good in order to get a high performance working system. However, for FAR value the other existing work has more accurate result in identifying fingerprint image compared to proposed work. Based from the experimental test, it shown that by using the proposed methods it is effective in order to identify low-quality and noises image with an accurate matching result and high performance system

A DoG based Approach for Fingerprint Image Enhancement

Fingerprints have been the most accepted tool for personal identification since many decades. It is also an invaluable tool for law enforcement and forensics for over a century, motivating the research in Automated fingerprint-based identification, an application of biometric system. The matching or identification accuracy using fingerprints has been shown to be very high. The theory on the uniqueness of fingerprint minutiae leads to the steps in studying the statistics of extracting the minutiae features reliably. Fingerprint images obtained through various sources are rarely of perfect quality. They may be degraded or noisy due to variations in skin or poor scanning technique or due to poor impression condition. Hence enhancement techniques are applied on fingerprint images prior to the minutiae point extraction to get sure of less spurious and more accurate minutiae points from the reliable minutiae location. This thesis focuses on fingerprint image enhancement techniques through histogram equalization applied locally on the degraded image. The proposed work is based on the Laplacian pyramid framework that decomposes the input image into a number of band-pass images to improve the local contrast, as well as the local edge information. The resultant image is passed through the regular methodologies of fingerprint, like ridge orientation, ridge frequency calculation, filtering, binarization and finally the morphological operation thinning. Experiments using different texture of images are conducted to enhance the images and to show a comparative result in terms of number of minutiae extracted from them along with the spurious and actual number existing in each enhanced image. Experimental results out performs well to overcome the counterpart of enhancement technique