Validation of Harris Detector and Eigen Features Detector

13Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Harris detector is one of the most common features detection for applications such as object recognition, stereo matching and target tracking. In this paper, a similar Harris detector algorithm is written using MATLAB and the performance is compared with MATLAB built in Harris detector for validation. This is to ensure that rewritten version of Harris detector can be used for Unmanned Aerial Vehicle (UAV) application research purpose yet can be further improvised. Another corner detector close to Harris detector, which is Eigen features detector is rewritten and compared as well using same procedures with same purpose. The simulation results have shown that rewritten version for both Harris and Eigen features detectors have the same performance with MATLAB built in detectors with not more than 0.4% coordination deviation, less than 4% & 5% response deviation respectively, and maximum 3% computational cost error.

References Powered by Scopus

A comprehensive review of current local features for computer vision

265Citations
N/AReaders
Get full text

Image features detection, description and matching

180Citations
N/AReaders
Get full text

Fast event-based Harris corner detection exploiting the advantages of event-driven cameras

130Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Identification of maize leaves infected by fall armyworms using UAV-based imagery and convolutional neural networks

68Citations
N/AReaders
Get full text

Research on Maize Seed Classification and Recognition Based on Machine Vision and Deep Learning

58Citations
N/AReaders
Get full text

Hybrid convolution neural network model for a quicker detection of infested maize plants with fall armyworms using UAV-based images

33Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Kok, K. Y., & Rajendran, P. (2018). Validation of Harris Detector and Eigen Features Detector. In IOP Conference Series: Materials Science and Engineering (Vol. 370). Institute of Physics Publishing. https://doi.org/10.1088/1757-899X/370/1/012013

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 3

50%

Lecturer / Post doc 2

33%

Professor / Associate Prof. 1

17%

Readers' Discipline

Tooltip

Engineering 3

60%

Design 1

20%

Computer Science 1

20%

Save time finding and organizing research with Mendeley

Sign up for free