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Scorpion image segmentation system

Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital ima...

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Main Authors: E, joseph, Aibinu, Abiodun Musa, B.A, sadiq, Bello Salau, H, Salami, Momoh Jimoh Eyiomika
Format: Article
Language:English
Published: IOP Publishing 2013
Subjects:
QA Mathematics
Online Access:http://irep.iium.edu.my/34607/1/1757-899X_53_1_012055.pdf
http://irep.iium.edu.my/34607/
http://iopscience.iop.org/1757-899X/53/1
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spelling my.iium.irep.346072015-08-13T13:03:30Z http://irep.iium.edu.my/34607/ Scorpion image segmentation system E, joseph Aibinu, Abiodun Musa B.A, sadiq Bello Salau, H Salami, Momoh Jimoh Eyiomika QA Mathematics Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection. IOP Publishing 2013 Article REM application/pdf en http://irep.iium.edu.my/34607/1/1757-899X_53_1_012055.pdf E, joseph and Aibinu, Abiodun Musa and B.A, sadiq and Bello Salau, H and Salami, Momoh Jimoh Eyiomika (2013) Scorpion image segmentation system. IOP Conference Series: Materials Science and Engineering, 53 (012055). pp. 1-9. ISSN 1757-8981 http://iopscience.iop.org/1757-899X/53/1 210.48.222.8
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
E, joseph
Aibinu, Abiodun Musa
B.A, sadiq
Bello Salau, H
Salami, Momoh Jimoh Eyiomika
Scorpion image segmentation system
description Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection.
format Article
author E, joseph
Aibinu, Abiodun Musa
B.A, sadiq
Bello Salau, H
Salami, Momoh Jimoh Eyiomika
author_facet E, joseph
Aibinu, Abiodun Musa
B.A, sadiq
Bello Salau, H
Salami, Momoh Jimoh Eyiomika
author_sort E, joseph
title Scorpion image segmentation system
title_short Scorpion image segmentation system
title_full Scorpion image segmentation system
title_fullStr Scorpion image segmentation system
title_full_unstemmed Scorpion image segmentation system
title_sort scorpion image segmentation system
publisher IOP Publishing
publishDate 2013
url http://irep.iium.edu.my/34607/1/1757-899X_53_1_012055.pdf
http://irep.iium.edu.my/34607/
http://iopscience.iop.org/1757-899X/53/1
_version_ 1643610651574140928
score 13.211869

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