An adaptive morphological filter for moving object segmentation

MUHAMMAD HAMEED SIDDIQI; MADALLAH ALRUWAILI; M. M. KAMRUZZAMAN; SAAD ALANAZI; SAID ELAIWAT; FAYADH ALENEZI

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An adaptive morphological filter for moving object segmentation

Author(s)

MUHAMMAD HAMEED SIDDIQI College of Computer and Information Sciences, Jouf University,Sakaka, Aljouf, Kingdom of Saudi, Arabia

MADALLAH ALRUWAILI College of Computer and Information Sciences, Jouf University,Sakaka, Aljouf, Kingdom of Saudi, Arabia

M. M. KAMRUZZAMAN College of Computer and Information Sciences, Jouf University,Sakaka, Aljouf, Kingdom of Saudi, Arabia

SAAD ALANAZI College of Computer and Information Sciences, Jouf University,Sakaka, Aljouf, Kingdom of Saudi, Arabia

SAID ELAIWAT College of Computer and Information Sciences, Jouf University,Sakaka, Aljouf, Kingdom of Saudi, Arabia

FAYADH ALENEZI Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka, Aljouf, Kingdom of Saudi Arabia

Abstract

This work presents a system that combined well-known morphological filters in order to find true moving regions from a sequence of images. For localizing the changed region, a block-based change segmentation process is proposed. This change region is naturally a coarse region and also contains some holes. To compensate this, we used an edge-based dilation to get an anisotropic expansion of the coarse image. Then the segmentation is generated using watershed algorithm. To prevent over segmentation, we used a specially weighted gradient image to achieve segmentation. Also, we removed some local minima from that gradient image. Finally, a fusion is applied on morphological filters. Furthermore, we calculated the coverage ratio of edge pixels of each segmented region. Comparing with a converge threshold, we determined whether the segmented region is truly belongs to a moving region or not. In the end, the experimental result demonstrated the validity of our proposed method.

Publication Details

Page(s) 2755-2762

DOI DOI not available

Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 98, Issue: 14, Year: 2020

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Keywords

Morphological Filter

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