Object Detection and Tracking using Watershed Segmentation and KLT Tracker

Tunirani Nayak; Nilamani Bhoi

Object Detection and Tracking using Watershed Segmentation and KLT Tracker

Tunirani Nayak *

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Nilamani Bhoi

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Object Detection and Tracking using Watershed Segmentation and KLT Tracker

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Abstract

In this paper, a moving object is extracted from a video using video object detection algorithm based on spatial and temporal segmentation. The technique begins with temporal segmentation in which edge map is extracted using edge operator. The initial binary mask is obtained by using morphological operation applied on initial edge map. The next phase is spatial segmentation where gradient image is obtained by multi-scale morphological operator. The modified gradient image is obtained by the operator applied over the current frame. At last, moving object is extracted by precisely and accurately by watershed segmentation which is performed on the modified gradient image. Again, morphological operation is applied on the output to get final binary mask. This binary mask is then complemented to yield the contour line of the video object. Using the binary mask, the video object is extracted from the video frames. After detection of video object, the object tracking is performed using Kanade-Lucas-Tomasi (KLT) feature tracker.

References

16 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Tunirani Nayak, Nilamani Bhoi. 2020. "Object Detection and Tracking using Watershed Segmentation and KLT Tracker". Global Journal of Computer Science and Technology, Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 20 (GJCST Volume 20 Issue F1).

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GJCST Volume 20 Issue F1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-F Classification I.4.8

Submission ReceivedDecember 13, 2019
Peer Review Double Blind
Handling Editor
Accepted January 3, 2020
Published January 15, 2020

Version of record

v1.2

Issue date

August 25, 2020

Language

English

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