Extending the Teknomo-Fernandez Background Image Generation Algorithm on the HSV Colour Space

Background subtraction, a procedure required in many video analysis applications such as object tracking , is dependent on the model background image. One efficient algorithm for background image generation is the Teknomo-Fernandez (TF) Algorithm, which uses modal values and a tournament-like strate...

Full description

Saved in:
Bibliographic Details
Main Authors: Abu, Patricia Angela R, Fernandez, Proceso L, Jr
Format: text
Published: Archīum Ateneo 2015
Subjects:
HSV
Online Access:https://archium.ateneo.edu/discs-faculty-pubs/75
https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1074&context=discs-faculty-pubs
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Ateneo De Manila University
id ph-ateneo-arc.discs-faculty-pubs-1074
record_format eprints
spelling ph-ateneo-arc.discs-faculty-pubs-10742020-05-06T08:21:32Z Extending the Teknomo-Fernandez Background Image Generation Algorithm on the HSV Colour Space Abu, Patricia Angela R Fernandez, Proceso L, Jr Background subtraction, a procedure required in many video analysis applications such as object tracking , is dependent on the model background image. One efficient algorithm for background image generation is the Teknomo-Fernandez (TF) Algorithm, which uses modal values and a tournament-like strategy to produce a good background image very quickly. A previous study showed that the TF algorithm can be extended from the original 3 frames per tournament (T F 3) to T F 5 and T F 7, resulting in increased accuracies at a cost of increased processing times. In this study, we explore extending the T F 3, T F 5 and T F 7 from the original RGB colour space to the HSV colour space. A ground truth model background image for HSV was also developed for comparing the performances between the TF implementations on the RGB and HSV channels. The results show that the TF algorithm generates accurate background images when implemented on the HSV colour space. However, the RGB implementations still exhibit higher accuracies than the corresponding HSV implementations. Finally, background subtraction was applied on the HSV generated background images. A comparison with other promising baseline techniques validates the competitiveness of the TF algorithm implemented on HSV channels. 2015-11-01T07:00:00Z text application/pdf https://archium.ateneo.edu/discs-faculty-pubs/75 https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1074&context=discs-faculty-pubs Department of Information Systems & Computer Science Faculty Publications Archīum Ateneo background subtraction boolean operation HSV mode values Computer Sciences Theory and Algorithms
institution Ateneo De Manila University
building Ateneo De Manila University Library
country Philippines
collection archium.Ateneo Institutional Repository
topic background subtraction
boolean operation
HSV
mode values
Computer Sciences
Theory and Algorithms
spellingShingle background subtraction
boolean operation
HSV
mode values
Computer Sciences
Theory and Algorithms
Abu, Patricia Angela R
Fernandez, Proceso L, Jr
Extending the Teknomo-Fernandez Background Image Generation Algorithm on the HSV Colour Space
description Background subtraction, a procedure required in many video analysis applications such as object tracking , is dependent on the model background image. One efficient algorithm for background image generation is the Teknomo-Fernandez (TF) Algorithm, which uses modal values and a tournament-like strategy to produce a good background image very quickly. A previous study showed that the TF algorithm can be extended from the original 3 frames per tournament (T F 3) to T F 5 and T F 7, resulting in increased accuracies at a cost of increased processing times. In this study, we explore extending the T F 3, T F 5 and T F 7 from the original RGB colour space to the HSV colour space. A ground truth model background image for HSV was also developed for comparing the performances between the TF implementations on the RGB and HSV channels. The results show that the TF algorithm generates accurate background images when implemented on the HSV colour space. However, the RGB implementations still exhibit higher accuracies than the corresponding HSV implementations. Finally, background subtraction was applied on the HSV generated background images. A comparison with other promising baseline techniques validates the competitiveness of the TF algorithm implemented on HSV channels.
format text
author Abu, Patricia Angela R
Fernandez, Proceso L, Jr
author_facet Abu, Patricia Angela R
Fernandez, Proceso L, Jr
author_sort Abu, Patricia Angela R
title Extending the Teknomo-Fernandez Background Image Generation Algorithm on the HSV Colour Space
title_short Extending the Teknomo-Fernandez Background Image Generation Algorithm on the HSV Colour Space
title_full Extending the Teknomo-Fernandez Background Image Generation Algorithm on the HSV Colour Space
title_fullStr Extending the Teknomo-Fernandez Background Image Generation Algorithm on the HSV Colour Space
title_full_unstemmed Extending the Teknomo-Fernandez Background Image Generation Algorithm on the HSV Colour Space
title_sort extending the teknomo-fernandez background image generation algorithm on the hsv colour space
publisher Archīum Ateneo
publishDate 2015
url https://archium.ateneo.edu/discs-faculty-pubs/75
https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1074&context=discs-faculty-pubs
_version_ 1681506576861495296