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

2012 ◽  
pp. 479-486 ◽  
Author(s):  
Li Shang ◽  
Jie Chen ◽  
Pin-Gang Su ◽  
Yan Zhou
Keyword(s):  
Corner Point ◽  
Detection Algorithm ◽  
Harris Corner ◽  
Roi Extraction ◽  
Point Detection

An Approach of Wavefront Identification for Traveling Wave Fault Location Based on Harris Corner Detector

2014 ◽  
Vol 960-961 ◽  
pp. 1100-1103
Author(s):  
Guang Bin Zhang ◽  
Hong Chun Shu ◽  
Ji Lai Yu
Keyword(s):  
Traveling Waves ◽  
Transmission Lines ◽  
Traveling Wave ◽  
Fault Location ◽  
Corner Point ◽  
Harris Corner ◽  
Corner Points ◽  
Simulated Test ◽  
Harris Corner Detector ◽  
Calculated Distance

Wavefront identification is important for traveling based fault location. In order to improve its reliability, a novel wavefront identification method based on Harris corner detector has been proposed in this paper. The principle of single-ended traveling wave fault location was briefly introduced at first, and the features of wavefronts generated by faults on transmission lines were analyzed. The arrival of traveling waves' wavefronts is considered as corner points in digital image of waveshape. The corner points can be extracted precisely by Harris corner detector, and both false corner points and non-fault caused disturbance can be eliminated according to the calculated distance between two neighbour corner points and the angle of the corner point. The proposed method is proved feasible and effective by digital simulated test.

scholarly journals A Doubly Stochastic Change Point Detection Algorithm for Noisy Biological Signals

2018 ◽  
Vol 8 ◽  
Author(s):  
Nathan Gold ◽  
Martin G. Frasch ◽  
Christophe L. Herry ◽  
Bryan S. Richardson ◽  
Xiaogang Wang
Keyword(s):  
Change Point ◽  
Detection Algorithm ◽  
Change Point Detection ◽  
Doubly Stochastic ◽  
Biological Signals ◽  
Point Detection

scholarly journals Corner point detection using nest moving average

1994 ◽  
Vol 27 (11) ◽  
pp. 1533-1537 ◽  
Author(s):  
Soo-Chang Pei ◽  
Ji-Hwei Horng
Keyword(s):  
Corner Point ◽  
Moving Average ◽  
Point Detection

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

Sensors ◽  
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.

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