Scorpion image segmentation system
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Date
2013
Journal Title
Journal ISSN
Volume Title
Publisher
IOP Publishing
Abstract
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 nonoverlapping 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
1 system will eliminate the problem associated with some of the existing manual approaches
presently in use for scorpion detection.
Description
Keywords
Scorpion image, Segmentation system
Citation
Joseph, E., Aibinu, A. M., Sadiq, B. A., Salau, H. B., & Salami, M. J. E. (2013). Scorpion image segmentation system. In IOP Conference Series: Materials Science and Engineering (Vol. 53, No. 1, p. 012055). IOP Publishing.