Fingerprint Sub-Classification and Singular Point Detection

1998 ◽  
Vol 12 (04) ◽  
pp. 407-422 ◽  
Author(s):  
Gustavo Drets ◽  
Hans Liljenström
Keyword(s):  
Singular Point ◽  
Detection Method ◽  
Field Pattern ◽  
Classification Procedure ◽  
Fingerprint Classification ◽  
Novel Approach ◽  
Directional Field ◽  
Forensic Expert ◽  
The Stability ◽  
Point Detection

This paper presents a novel approach to fingerprint singular point detection. Singular points (cores and deltas) are used for fingerprint classification, sub-classification and registration. This method exploits the stability of the directional field pattern extracted from singular point regions at different resolution levels. The procedure is invariant to translations, scaling and small rotations. A fingerprint sub-classification procedure was built based on the proposed singular point detection method. Two kinds of tests were conducted on a subset consisting of 955 NIST-14 fingerprint images. First, automatic and forensic expert sub-classifications were compared. Second, the consistency of the proposed method was measured comparing automatic sub-classification for two different rolls of the same fingerprint.

scholarly journals A Customized Semantic Segmentation Network for the Fingerprint Singular Point Detection

2020 ◽  
Vol 10 (11) ◽  
pp. 3868
Author(s):  
Jiong Chen ◽  
Heng Zhao ◽  
Zhicheng Cao ◽  
Fei Guo ◽  
Liaojun Pang
Keyword(s):  
Singular Point ◽  
Semantic Segmentation ◽  
Singular Points ◽  
Detection Methods ◽  
Orientation Field ◽  
Global Features ◽  
Fingerprint Image ◽  
Detection Rates ◽  
Fingerprint Classification ◽  
Point Detection

As one of the most important and obvious global features for fingerprints, the singular point plays an essential role in fingerprint registration and fingerprint classification. To date, the singular point detection methods in the literature can be generally divided into two categories: methods based on traditional digital image processing and those on deep learning. Generally speaking, the former requires a high-precision fingerprint orientation field for singular point detection, while the latter just needs the original fingerprint image without preprocessing. Unfortunately, detection rates of these existing methods, either of the two categories above, are still unsatisfactory, especially for the low-quality fingerprint. Therefore, regarding singular point detection as a semantic segmentation of the small singular point area completely and directly, we propose a new customized convolutional neural network called SinNet for segmenting the accurate singular point area, followed by a simple and fast post-processing to locate the singular points quickly. The performance evaluation conducted on the publicly Singular Points Detection Competition 2010 (SPD2010) dataset confirms that the proposed method works best from the perspective of overall indexes. Especially, compared with the state-of-art algorithms, our proposal achieves an increase of 10% in the percentage of correctly detected fingerprints and more than 16% in the core detection rate.

scholarly journals A Novel Approach to Fabricate Foam Ceramics from Steel Slag

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Yu Zheng ◽  
Xudong Luo ◽  
Jinlong Yang ◽  
Wenlong Huo ◽  
Chi Kang
Keyword(s):  
Compressive Strength ◽  
Ph Value ◽  
Steel Slag ◽  
Raw Material ◽  
Solid Loading ◽  
Insulation Material ◽  
Ceramic Foams ◽  
Novel Approach ◽  
The Stability ◽  
First Time

A novel approach is used for fabricating steel slag foam ceramics based on the particle-stabilized foaming method. In this work, steel slag was used as the raw material and propyl gallate (PG) was used as the surface modifier. For the first time, steel slag ceramic foams were successfully fabricated based on particle-stabilized foams. The results show that the stability of the ceramic foams was closely related to the pH value and PG concentration. The porosity and compressive strength could be controlled by changing the solid loading of steel slag and sintering temperature. The porosity of steel slag foam ceramics ranged from 85.6% to 62.53%, and the compressive strength was from 1.74 MPa to 10.42 MPa. The thermal conductivity of steel slag foam ceramics was only 0.067 W (m·K)−1, which shows that it could be used as a thermal insulation material.

Design of Swimming Pool Temperature Dot Matrix Screen Display

2014 ◽  
Vol 556-562 ◽  
pp. 2208-2211
Author(s):  
Xue Feng Yang
Keyword(s):  
Water Temperature ◽  
Real Time ◽  
Room Temperature ◽  
Detection Method ◽  
Swimming Pool ◽  
Real Time Monitoring ◽  
Real Time Processing ◽  
The Core ◽  
Swimming Pool Water ◽  
Point Detection

According to the need of the real-time monitoring and displaying of the environment in many areas,to put forward a method of temperature monitoring and displaying, using STC11F32XE microcontroller as the core controller, DS18B20 as temperature acquisition chip, 32X64LED dot matrix screen as a display screen,using the mothod of multi point detection method,real-time monitoring of swimming pool water temperature and room temperature, real-time displaying of Multipoint collecting information, Real time processing the detected temperature, the page display to multipoint temperature display through the wireless remote control module,the system will alarm When the water temperature is too high or too low, to remind managers of real-time processing.To design a clear temperature display for the swimming pool,real time monitoring and controlling is very convenient,after the experimental verification, the system reaches the anticipative goal,the system is an ideal and effective.

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