scholarly journals An Analysis and Implementation of the Harris Corner Detector

2018 ◽  
Vol 8 ◽  
pp. 305-328 ◽  
Author(s):  
Javier Sánchez ◽  
Nelson Monzón ◽  
Agustín Salgado
Keyword(s):  
Harris Corner ◽  
Harris Corner Detector

A fast approximate Harris corner detector

2009 ◽  
Author(s):  
Bing Han ◽  
Jiyin Sun ◽  
Jing Liu
Keyword(s):  
Harris Corner ◽  
Harris Corner Detector

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.

Sliding Window Based Fast Corner Matching Palmprint Authentication

2011 ◽  
Vol 1 (3) ◽  
pp. 16-34
Author(s):  
Jyoti Malik ◽  
G. Sainarayanan ◽  
Ratna Dahiya
Keyword(s):  
Response Time ◽  
Hamming Distance ◽  
Recognition Rate ◽  
Sliding Window ◽  
Phase Congruency ◽  
Window Method ◽  
Harris Corner ◽  
Sliding Window Method ◽  
Authentication System ◽  
Harris Corner Detector

Authentication time is the main and important part of the authentication system. Normally the response time should be fast but as the number of persons in the database increases, there is probability of more response time taken for authentication. The need of fast authentication system arises so that authentication time (matching time) is very less. This paper proposes a sliding window approach to make fast authentication system. The highlight of sliding window method is constant matching time, fast and can match translated images also. Several palmprint matching methods like match by correlation etc. are dependent upon the number of corners detected and so is the matching time. In sliding window method, matching time is constant as the numbers of matching operations are limited and the matching time is independent of the number of corners detected. The palmprint corner features extracted using two approaches Phase Congruency Corner Detector and Harris Corner Detector are binarized so that only useful information (features) is matched. The two approaches of Phase Congruency Corner Detector and Harris Corner Detector, when matched with hamming distance using sliding window can achieve recognition rate of 97.7% and 97.5% respectively.

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