Anomaly detection in multi-temporal infrared thermography

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Anomaly detection is an important tool in various types of image processing and was widely investigated in the area of hyperspectral imaging. This research focuses on anomaly detection within multi temporal thermal images. We used three types of datasets; I) anomaly-free images, II) synthetically anomaly images, III) images with small metal objects, both buried and exposed. In this article, we introduce a new algorithm called RXmin in which we examine the metric distance between the suspected pixel to other pixels in the image. In contrast to visible light imagery, this method, when operating in the infrared is indifferent to the presence of sunlight and therefore can be used during the night. The proposed algorithms are general in nature and can be used for other types of information or functions such as video analysis, array processing, seismic signal processing etc.

Original languageEnglish
Title of host publication2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479959877
DOIs
StatePublished - 1 Jan 2014
Event2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 - Eilat, Israel
Duration: 3 Dec 20145 Dec 2014

Publication series

Name2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014

Conference

Conference2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014
Country/TerritoryIsrael
CityEilat
Period3/12/145/12/14

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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