Home » Education » BRAIN: Efficient Filtering of Noisy Fingerprint Images


February 2016
« Dec   Mar »

Read these articles

  • LiBRI: On Studying Teacher’s Self EsteemLiBRI: On Studying Teacher’s Self Esteem
    Baghli Asmaa is bringing to light a new discussion in LiBRI journal: On Studying Teacher’s Self Esteem Based on Revised Janis Scale Application. An actual and controversial research that brings out some intensely sought answers …
  • LiBRI: The Free Choice for Absurd Rebellion in Nineteen Eighty-FourLiBRI: The Free Choice for Absurd Rebellion in Nineteen Eighty-Four
    A novel such as “Nineteen Eighty-Four” has determined critics to never stop analysing in as many angles as possible this masterpiece, so as to reveal the most profound meanings that George Orwell wanted to transmit …
  • Hello dear scholars!
    Academia EduSoft is a website for researchers, scholars, academic staff, and students.
  • SMART 2017 International ConferenceSMART 2017 International Conference
    SMART 2017 – Scientific Methods in Academic Research and Teaching is an international conference, which will be held in Timișoara, Romania, between September 8 and September 9, 2017. This year, the conference will focus on three …
  • BRAIN Journal – Questioning, Context-Sensitiveness and Philosophical InquiryBRAIN Journal – Questioning, Context-Sensitiveness and Philosophical Inquiry
    Inquiry is an official process to discover the facts about something bad that has happened. In this paper the authors aim to explain that context-sensitiveness is a very important aspect of philosophical inquiry, specifically through …
  • BRAIN Volume 8, Issue 1 (April 2017) indexed in Web of ScienceBRAIN Volume 8, Issue 1 (April 2017) indexed in Web of Science
    We are happy to let you know about the recent indexation in Web of Science of the issue 1 (April 2017) of the 8th volume of our international journal BRAIN – Broad Research in Artificial …
  • About Machine Ethics and Artificial Intelligence SafetyAbout Machine Ethics and Artificial Intelligence Safety
      We are all familiar with the movies in which robots take control over humans and then chaos is brought into the world just because these forms of artificial intelligence became too developed. But is …
  • SMART 2017 International Conference
    Here are some of the photos that were taken at SMART 2017 International Conference. You can find more on our facebook page. We want to thank all of the participants for the effort placed in their research …
  • BRAIN: Image Finder Mobile Application Based on Neural NetworksBRAIN: Image Finder Mobile Application Based on Neural Networks
    Technology has become more than a phenomenon used for innovation, it is now a science put in the service of making human life easier. If in the past, taking a picture of yourself required a …
  • BRAIN: Classification of Human EmotionBRAIN: Classification of Human Emotion
    An innovative research in BRAIN journal, Classification of Human Emotion from Deap EEG Signal Using Hybrid Improved Neural Networks with Cuckoo Search, academic article provided by M. Sreeshakthy and J. Preethi, both professors at Anna …
  • BRAIN: Participative Teaching with Mobile Devices and Social Networks for K-12 ChildrenBRAIN: Participative Teaching with Mobile Devices and Social Networks for K-12 Children
    BRAIN journal exhibits a creative study on the Participative Teaching, utilizing strategies like Mobile Devices and Social Network for K-12 Children. Livia Stefan and Dragos Gheorghiu from Bucharest, Romania have inquired about the participatory pedagogical investigate, …
  • BRAND: Pricing in Multi-Heston Framework
    BRAND journal provides a very interesting article written by Tiberiu Socaciu from Stefan cel Mare University of Suceava, Faculty of Economics. This article displays a definitive in determining an estimating system’s multi-Heston. Fundamentally, he utilizes the …


BRAIN: Efficient Filtering of Noisy Fingerprint Images

Fingerprint identification is an imperative field in the wide space of biometrics with numerous applications, in various zones such as: judicial, cell telephones, access systems, airports.

There are many elaborated algorithms for fingerprint identification, but none of them can guarantee that the results of identification are always 100 % accurate.

Professor Maria Liliana Costin, from Babes-Bolyai University, in Cluj Romania, demonstrates through rigurous research the successful completion of the noisy digital image filtering.

Selection of filtered images with the 9 algorithms and the 2 methods of classification
Selection of filtered images with the 9 algorithms and the 2 methods of classification

The research published in BRAIN journal, shows an initial phase in a fingerprint image analysing process that comprises in the pre-handling or filtering. On the off chance that the outcome after this stride is not by a decent quality the forthcoming ID procedure can come up short. A major difficulty can show up if there should arise an occurrence of unique mark recognizable proof if the pictures that ought to be distinguished from a fingerprint image  database are noisy with various sort of commotion.

The decision about the best filtered pictures of an arrangement of 9 algorithms is made with a double technique of fuzzy and aggregation model. The researcher is proposing through this paper an arrangement of 9 filters with various oddity intended for handling the computerized pictures utilizing the accompanying strategies: quartiles, medians, average, thresholds and histogram equalization, connected everywhere throughout the picture or locally on small areas. At last the measurements uncover the arrangement and positioning of the best calculations.

The identification of individuals based on biometrics are made by different methods like: face recognition, palm recognition, voice recognition or handwriting recognition but one of the most usual approaches consists in the fingerprint based identification.

Some of the most important implementations of fingerprint algorithms are the IAFIS-Integrated Automated Fingerprint Identification System used by the FBI, which will be followed by the Next Generation Identification system1 developed by Lockheed Martin in partnership with Safran and also commercial applications implemented in: mobile phone applications, different operating systems like: Apple-iOS, Android, access systems and airports.

Automatic identification based on fingerprints can be synthesized into five distinct phases: pre-processing, feature extraction, feature measurement, classification and matching. At the step of pre-processing the challenge is to find the best methods for enhancing images, taking into consideration the accuracy and the time for execution.

Designing  the model included three noteworthy steps: characterizing the arrangement of channels modified for the arrangement of unique mark pictures, characterizing the equipment for the programmed choice of the best filter for every situation lastly the order in the wake of handling an arrangement of pictures. In the annex, the researchers were uncovered to a limited extent the aftereffect of every channel and there assessment and picking the picture that will be utilized as a part of ensuing phases of examination inside of the significance of robotizing the whole procedure of ID taking into account fingerprints. As a continuation of the computerization process there is planned to assess the fuzzy and statistical parameters with more advanced strategies such as neural systems.

Read more here!

Diana-Elena Melinte