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Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV

: This research paper is about method of detection of free region and obstacle region by combining image segmentation and frame subtraction method. The application will be further study to be used by Unmanned Aerial Vehicles (UAVs). This method intends to minimize the weight of UAV by avoiding heavy...

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Main Authors: Abdul Aziz, Muhamad Wafi, Ramli, Muhammad Faiz
Format: Article
Language:English
Published: 2024
Subjects:
T Technology (General)
Online Access:http://eprints.uthm.edu.my/11000/1/J17495_e04854e54a2dc6162e59cab99223915b.pdf
http://eprints.uthm.edu.my/11000/
http://dx.doi.org/10.12785/ijcds/150135
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spelling my.uthm.eprints.110002024-05-20T01:38:10Z http://eprints.uthm.edu.my/11000/ Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV Abdul Aziz, Muhamad Wafi Ramli, Muhammad Faiz T Technology (General) : This research paper is about method of detection of free region and obstacle region by combining image segmentation and frame subtraction method. The application will be further study to be used by Unmanned Aerial Vehicles (UAVs). This method intends to minimize the weight of UAV by avoiding heavy sensors. Objective of this research is to utilize the pixel expansion of object to find free region. K-means segmentation will be used to separate the interest area from the background. Then, segmented image frame will be subtracted and then divided into several grids and the amount of subtracted pixel that has been set into yellow and black color of each grid will be calculated with respect to distance given. The expansion of pixel will be detected as, the distance between image frame coming closer, number of obstacle pixel will be higher. The application of simple LIDAR that emits single ray to frontal obstacle will initiate the camera to capture image frame to be further analyze. Experiment was carried out in close environment with different cases and total of 100 images has been captured that consist of texture obstacle, texture-less obstacle, and multiple obstacles. The findings showed bearable results as the free region detection is 88.0% for texture obstacle and up to 84.0% of free region were successfully detected for texture-less obstacle. Due to lack of cues and texture in texture-less object, the algorithm had difficulties detecting the center of object that expands in static form. 2024 Article PeerReviewed text en http://eprints.uthm.edu.my/11000/1/J17495_e04854e54a2dc6162e59cab99223915b.pdf Abdul Aziz, Muhamad Wafi and Ramli, Muhammad Faiz (2024) Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV. International Journal of Computing and Digital Systems, 15 (1). pp. 451-463. http://dx.doi.org/10.12785/ijcds/150135
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Abdul Aziz, Muhamad Wafi
Ramli, Muhammad Faiz
Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV
description : This research paper is about method of detection of free region and obstacle region by combining image segmentation and frame subtraction method. The application will be further study to be used by Unmanned Aerial Vehicles (UAVs). This method intends to minimize the weight of UAV by avoiding heavy sensors. Objective of this research is to utilize the pixel expansion of object to find free region. K-means segmentation will be used to separate the interest area from the background. Then, segmented image frame will be subtracted and then divided into several grids and the amount of subtracted pixel that has been set into yellow and black color of each grid will be calculated with respect to distance given. The expansion of pixel will be detected as, the distance between image frame coming closer, number of obstacle pixel will be higher. The application of simple LIDAR that emits single ray to frontal obstacle will initiate the camera to capture image frame to be further analyze. Experiment was carried out in close environment with different cases and total of 100 images has been captured that consist of texture obstacle, texture-less obstacle, and multiple obstacles. The findings showed bearable results as the free region detection is 88.0% for texture obstacle and up to 84.0% of free region were successfully detected for texture-less obstacle. Due to lack of cues and texture in texture-less object, the algorithm had difficulties detecting the center of object that expands in static form.
format Article
author Abdul Aziz, Muhamad Wafi
Ramli, Muhammad Faiz
author_facet Abdul Aziz, Muhamad Wafi
Ramli, Muhammad Faiz
author_sort Abdul Aziz, Muhamad Wafi
title Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV
title_short Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV
title_full Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV
title_fullStr Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV
title_full_unstemmed Region Detection Technique Using Image Subtraction and Pixel Expansion Cue for Obstacle Detection System on Small – Sized UAV
title_sort region detection technique using image subtraction and pixel expansion cue for obstacle detection system on small – sized uav
publishDate 2024
url http://eprints.uthm.edu.my/11000/1/J17495_e04854e54a2dc6162e59cab99223915b.pdf
http://eprints.uthm.edu.my/11000/
http://dx.doi.org/10.12785/ijcds/150135
_version_ 1800094637953646592
score 13.211869

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