Browsing by Author "Salau, Bello H."

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    Development of an intelligent scorpion detection technique using vibration analysis
    (IEEE, 2014-06-03) Aibinu, A. M.; Sadiq, B. A.; Joseph, E.; Salau, Bello H.; Salami, Momoh-Jimoh E.
    A possible solution to address the problem of Scorpion stings is the capability of detecting its presence earlier before it stings. This paper presents efforts in Scorpion detection using substrate vibration modelling approach. An eight stage approach has been presented in this work. Using sinusoidal signal, signal representing Scorpion behaviour was firstly sampled and then amplified before transmitting to a nearby receiving module. The received signal undergoes filtering for noise removal before being modelled for coefficients determination. The computed coefficients were then clustered for analysis of behavioural determination. Results obtained in this work show that the proposed technique can be used for Scorpion detection.
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    Performance Analysis of Clustering Based Genetic Algorithm
    (IEEE, 2016-07-26) Najeeb, Athaur R.; Aibinu, A. M.; Nwohu, M. N.; Salami, Momoh-Jimoh E.; Salau, Bello H.
    In this work, performance analysis of Clustering based Genetic Algorithm (CGA) proposed in the literature has been undertaken. The proposed CGA on which the performance analysis of this paper is based involve the use of two centroids based clustering technique as a new method of chromosomes selection at the reproduction stage in a typical Genetic Algorithm. Population Control and Polygamy mating techniques were introduced to improve the performance of the algorithm. Results obtained from the determination of optimal solutions to the: Sphere, Schwefel 2.4, Beale and another known optimization functions carried out in this work shows that the proposed CGA converges to global solutions within few iterations and can also be adopted for function optimization aside from the route optimization problem previously reported in Literature.
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    Scorpion image segmentation system
    (IOP Publishing, 2013) Joseph, E.; Aibinu, A. M.; Sadiq, B. A.; Salau, Bello H.; Salami, Momoh-Jimoh E.
    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.