Mohd Fikri Che Husin
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Preferred name
Mohd Fikri Che Husin
Official Name
Mohd Fikri , Che Husin
Alternative Name
Husin, Mohd Fikri Che
Husin, M. F.C.
Che Husin, Mohd Fikri
Main Affiliation
Scopus Author ID
57209776777
Researcher ID
EXZ-9092-2022

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  • Publication
    Image processing for paddy disease detection using K-means clustering and GLCM algorithm
    ( 2021-12)
    A. F. A. Ahmad Effendi
    ;
    Mohd Nazrin Md Isa
    ;
    Muhammad Imran Ahmad
    ;
    Mohd Fikri Che Husin
    ;
    Siti Zarina Md Naziri
    The traditional human-based visual quality inspection approach in agriculture is unreliable and uneven due to various variables, including human errors. In addition to the lengthy processing durations, the traditional method necessitates plant disease diagnostic experts. On the other hand, existing image processing approaches in agriculture produce low-quality output images despite having a faster computation time. As a result, a more comprehensive set of image processing algorithms was used to improve plant disease detection. This research aims to develop an efficient method for detecting leaf diseases using image processing techniques. In this work, identifying paddy diseases based on their leaves involved a number of image-processing stages, including image pre-processing, image segmentation, feature extraction, and eventually paddy leaf disease classification. The proposed work targeted the segmentation step, whereby an input image is segmented using the K-Means clustering with image scaling and colour conversion technique in the pre-processing stage. In addition, the Gray Level Co-occurrence Matrix technique (GLCM) is used to extract the features of the segmented images, which are used to compare the images for classification. The experiment is implemented in MATLAB software and PC hardware to process infected paddy leaf images. Results have shown that K-Means Clustering and GLCM are capable without using the hybrid algorithm on each image processing phase and are suitable for paddy disease detection.
      1  74
  • Publication
    Fabrication of 110 Silicon Nanowire Oriented with Direct Band Gap
    ( 2020-12-18)
    Tijjani Adam
    ;
    Dhahi T.S.
    ;
    Khairul Affendi Rosli
    ;
    Jaafar M.
    ;
    Jaafar R.
    ;
    Mohd Fikri Che Husin
    ;
    Mohd Norhafiz Hashim
    ;
    Mohamad Rizal Abdul Rejab
    Today, the challenges of getting fast switching semiconductor device based device is the phonon generation mechanism for light-emitting by device such as diodes. The increase in efficiency of the device determine by the green light part of the emitted light spectrum. Silicon nanowire growth in the direction of 110 structure has indirect band gap, which tremendously improved the green emission efficiency at the lower Nano regime. Several band structure calculations have be predicted direct band for 110 growth silicon nanowire. Thus, the study report the fabrication of silicon nanowires with diameter between 20 to 50nm which demonstrate the direct nature of the band gap. A strong photoluminescence at wave spectrum of 597 nm with micro-second lifetime indicating it direct band gap. This study have demonstrated new nanostructure engineering based on silicon nanowire orientation which will allow new ways getting silicon nanowire functionality.
      7  22