Fingerprint Core Point Detection Algorithm using Orientation Field Based Multiple Features

<abstract> <p>Singular point detection is a primary step in fingerprint recognition, especially for fingerprint alignment and classification. But in present there are still some problems and challenges such as more false-positive singular points or inaccurate reference point localization. This paper proposes an accurate core point localization method based on spatial domain features of fingerprint images from a completely different viewpoint to improve the fingerprint core point displacement problem of singular point detection. The method first defines new fingerprint features, called furcation and confluence, to represent specific ridge/valley distribution in a core point area, and uses them to extract the innermost Curve of ridges. The summit of this Curve is regarded as the localization result. Furthermore, an approach for removing false Furcation and Confluence based on their correlations is developed to enhance the method robustness. Experimental results show that the proposed method achieves satisfactory core localization accuracy in a large number of samples.</p> </abstract>

Download Full-text

ROI Extraction of Palmprint Images Using Modified Harris Corner Point Detection Algorithm

Lecture Notes in Computer Science - Intelligent Computing Theories and Applications ◽

10.1007/978-3-642-31576-3_61 ◽

2012 ◽

pp. 479-486 ◽

Cited By ~ 5

Author(s):

Li Shang ◽

Jie Chen ◽

Pin-Gang Su ◽

Yan Zhou

Keyword(s):

Corner Point ◽

Detection Algorithm ◽

Harris Corner ◽

Roi Extraction ◽

Point Detection

Download Full-text

A Detection Algorithm of Singular Points in Fingerprint Images Combining Curvature and Orientation Field

Intelligent Computing in Signal Processing and Pattern Recognition - Lecture Notes in Control and Information Sciences ◽

10.1007/11816515_62 ◽

2006 ◽

pp. 593-599

Author(s):

Xiaolong Zheng ◽

Yangsheng Wang ◽

Xuying Zhao

Keyword(s):

Detection Algorithm ◽

Singular Points ◽

Orientation Field

Download Full-text

Vital Block and Vital Sign Server for ECG and Vital Sign Monitoring in a Portable u-Vital System

Sensors ◽

10.3390/s20041089 ◽

2020 ◽

Vol 20 (4) ◽

pp. 1089

Author(s):

Tae Wuk Bae ◽

Kee Koo Kwon ◽

Kyu Hyung Kim

Keyword(s):

Real Time ◽

Vital Sign ◽

Vital Signs ◽

Detection Algorithm ◽

Smart Device ◽

Blood Oxygen Saturation ◽

Real Time Processing ◽

Non Invasive ◽

Wireless Protocols ◽

Point Detection

An important function in the future healthcare system involves measuring a patient’s vital signs, transmitting the measured vital signs to a smart device or a management server, analyzing it in real-time, and informing the patient or medical staff. Internet of Medical Things (IoMT) incorporates information technology (IT) into patient monitoring device (PMD) and is developing traditional measurement devices into healthcare information systems. In the study, a portable ubiquitous-Vital (u-Vital) system is developed and consists of a Vital Block (VB), a small PMD, and Vital Sign Server (VSS), which stores and manages measured vital signs. Specifically, VBs collect a patient’s electrocardiogram (ECG), blood oxygen saturation (SpO2), non-invasive blood pressure (NiBP), body temperature (BT) in real-time, and the collected vital signs are transmitted to a VSS via wireless protocols such as WiFi and Bluetooth. Additionally, an efficient R-point detection algorithm was also proposed for real-time processing and long-term ECG analysis. Experiments demonstrated the effectiveness of measurement, transmission, and analysis of vital signs in the proposed portable u-Vital system.

Download Full-text