Browsing Mohd Yusoff Mashor, Prof. Dr. by Author "khusairi@ppinang.uitm.edu.my"
Now showing items 1-12 of 12
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3D object recognition using MANFIS network with orthogonal and non-orthogonal moments
M. Khusairi, Osman; Mohd Yusoff, Mashor; M. Rizal, Arshad; Zuraidi, Saad (Institute of Electrical and Electronics Engineering (IEEE), 2009-03-06)This paper addresses a performance analysis of two well known moments, namely Hu's moments and Zernike's moments for 3D object recognition. Hu's moments and Zernike's moments are the non-orthogonal and orthogonal moments ... -
Application of fuzzy c-mean clustering technique for mycobacterium tuberculosis detection in Ziehl-Neelsen stained tissue images
Muhammad Khusairi, Osman; Mohd Yusoff, Mashor, Prof. Dr. (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)Automatic detection of Mycobacterium tuberculosis improves accuracy, sensitivity and efficiency of diagnosis compared to manual method. However, the process is difficult, especially in Zeihl-Neelsen stained tissue ... -
Colour image enhancement using bright and dark stretching techniques for tissue based Tuberculosis Bacilli detection
Muhammad Khusairi, Osman; Yusoff, Mashor; Hasnan, Jaafar (Universiti Malaysia Perlis, 2009-10-11)Tuberculosis is a serious disease caused by infection with the germ Mycobacterium tuberculosis. Sputum sample analysis is a common method for TB bacilli detection. In some cases, tissue from the suspected system is also ... -
Colour image segmentation of tuberculosis bacilli in Ziehl-Neelsen-stained tissue images using moving K-Mean clustering procedure
M. K. Osman; Mohd Yusoff, Mashor, Prof Madya Dr.; Z. Saad; H. Jaafar (Institute of Electrical and Electronics Engineers (IEEE), 2010-05)Segmentation of tuberculosis bacilli in Zeihl-Neelsen tissue slide images is a crucial step in computerassisted tuberculosis bacilli detection. In this paper, an automatic colour image segmentation using moving k-mean ... -
Detection of mycobacterium tuberculosis in tissue using k-Nearest neighbour and fuzzy k-Nearest neighbour classifiers
Muhammad Khusairi, Osman; Mohd Yusoff, Mashor, Prof. Dr.; Hasnan, Jaafar (Universiti Malaysia Perlis (UniMAP), 2012-06-18)Early detection and treatment are the most promising way to increase a patient's chance of survival from TB disease, reduce the duration and cost of treatment, and prevent the disease from spreading. Currently, microscopic ... -
Detection of tubercle bacilli in Ziehl-Neelsen stained tissue slide images using Hu’s moment invariants and artificial neural network
Mohammad Khusairi, Osman; Mohd Yusoff, Mashor, Prof. Dr.; Hasnan, Jaafar (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)Early detection of tuberculosis infection is the key to successful treatment and control of the disease. Manual screening by light microscopy is the most widely used for tubercle bacilli detection but it is time ... -
Detection of tuberculosis bacilli in tissue slide images using HMLP network trained by Extreme Learning Machine
Muhammad Khusairi, Osman; Mohd Yusoff, Mashor, Prof. Dr.; Hasnan, Jaafar, Prof. (Kauno Technologijos Universitetas, 2012-04)This paper proposes an automated detection of tuberculosis bacilli in Ziehl-Neelsen-stained tissue slides using image processing and neural network. Image segmentation using CY-based colour filter and k-mean clustering ... -
Injected fuel flow forecasting with Online Sequential Extreme Learning Machine
Zuraidi, Saad; Muhammad Khusairi, Osman; Mohd Yusoff, Mashor, Prof. Dr. (Universiti Malaysia Perlis (UniMAP), 2012-06-18)This study deals with Online Sequential Extreme Learning Machine (OS-ELM) modeling of a gasoline engine to predict the injected fuel flow of the engine. The single hidden layer feedforward networks (SLFN) trained by ... -
Online sequential extreme learning machine for classification of Mycobacterium tuberculosis in Ziehl-Neelsen stained tissue
Muhammad Khusairi, Osman; Mohd Yusoff, Mashor, Prof. Dr.; Hasnan, Jaafar, Assoc. Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)The application of image processing and artificial intelligence for computer-aided tuberculosis (TB) diagnosis has received considerable attention over the past several years and still is an active research area. Several ... -
Performance comparison of clustering and thresholding algorithms for tuberculosis bacilli segmentation.
Mohammad Khusairi, Osman; Mohd Yusoff, Mashor, Prof. Dr.; Hasnan, Jaafar (Institute of Electrical and Electronics Engineers (IEEE), 2012-05-14)Image segmentation is a key step in most medical image analysis. However, the process is particularly difficult due to limitation of the imaging equipments and variation in biological system. Therefore, accurate and robust ... -
Segmentation of tuberculosis bacilli in Ziehl-Neelsen tissue slide images using Hibrid Multilayered Perceptron network
M. K., Osman; Mohd Yusoff, Mashor, Prof. Madya Dr.; Jaafar, H. (Institute of Electrical and Electronics Engineers (IEEE), 2010-05-10)Segmentation of Zeihl-Neelsen tissue slide images is an important step in computer-assisted tuberculosis bacilli detection. In Zeihl-Neelsen tissue slide image, colour is the most prominent feature to detect the presence ... -
Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine
Muhammad Khusairi, Osman; Mohd Yusof, Mashor, Prof. Dr.; Hasnan, Jaafar, Assoc. Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-04)This paper describes an approach to automate the detection and classification of tuberculosis (TB) bacilli in tissue section using image processing technique and feedforward neural network trained by Extreme Learning ...