Aimi Salihah Abdul Nasir
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Preferred name
Aimi Salihah Abdul Nasir
Official Name
Aimi Salihah, Abdul Nasir
Alternative Name
Abdul Nasir, Aimi Salihah
Abdul-Nasir, Aimi Salihah
Nasir, Aimi Salihah Abdul
Main Affiliation
Scopus Author ID
57219027157
Researcher ID
AAG-1747-2021

Research Output
Now showing 1 - 5 of 5
  • Publication
    Analysis of the performance of SLIC super-pixel toward pre-segmentation of soil-transmitted helminth
    (AIP Publishing, 2023)
    Loke Siew Wen
    ;
    Lim Chee Chin
    ;
    Aimi Salihah Abdul Nasir
    ;
    Norhanis Ayunie Ahmad Khairudin
    ;
    Chong Yen Fook
    ;
    Mohd Yusoff Mashor
    ;
    Zeehaida Mohamed
    Soil-Transmitted Helminth (STH) infections are one of the most severe health issues in the world including Malaysia and frequently happened in an unsanitary environment within the children group. The helminth infections are diagnosed by inspecting the faeces samples manually through light microscope. However, the manual inspection method to diagnose the helminth egg is a time-consuming and challenging process especially when are huge number of samples. To increase the efficiency and accuracy of the diagnosis, an analysis of super-pixel segmentation with different parameter adjustments on four different species was carried out. This work described a Simple Linear Iterative Clustering (SLIC) super-pixel algorithm that uses different parameter settings to explore more parasites image features for a better segmentation process in the future and to analyse the effect of different SLIC parameter settings towards the pre-segmentation process. There is total 80 images collected from the four helminth egg species which are Ascaris Lumbricoides Ova (ALO), Enterobius Vermicularis Ova (EVO), Hookworm Ova (HWO) and Trichuris Trichiura Ova (TTO). The proposed approach is divided into three steps. First, the images with various lighting conditions are enhanced by the partial contrast stretching (PCS) technique. The simple linear iterative clustering (SLIC) super-pixel algorithm was implemented to the enhanced images as a pre-segmentation algorithm to form super-pixel images. Lastly, image quality assessment will be performed on the SLIC images. The SLIC parameter compactness of super-pixel, m of 5 and number of super-pixels, k of 1000 was selected because they generate the greatest PSNR value, indicating that this combination of parameters could produce high-quality images. In future, a more in-depth analysis of the parameter k and m, which impacts the form of each super-pixel and the pre-segmentation process, might improve the recommended approach.
  • Publication
    Fast k-means clustering algorithm for malaria detection in thick blood smear
    ( 2020-11-09)
    Aris T.A.
    ;
    Aimi Salihah Abdul Nasir
    ;
    Lim Chee Chin
    ;
    Haryati Jaafar
    ;
    Mohamed Z.
    Lots of people all over the world is threaten by a popular blood infection illness that is called as malaria. According to this fact, immediate diagnosis tests are essential to avoid the malaria parasites from expanding in every part of the body. Malaria detection is based on parasitic count process on thick blood smear samples. Anyhow, this mechanism consist the chances of misinterpretation of parasites on behalf to human flaws. Thus, this research objective is to investigate the segmentation performance for improving malaria detection in thick blood smear images through fast k-means clustering algorithm on various color models. In this research, fast kmeans clustering is used because of its advantage which is no need to retrain cluster center that causes time taken to train the image cluster centers is reduce. Meanwhile, different color models have been utilized in order to identify the most relevant color model that obviously highlight the parasites. Five varied color models namely RGB, XYZ, HSV, YUV and CMY are selected and 15 color components namely R, G, B, X, Y, Z, H, S, V, Y, U, V, C, M and Y component have been derived with the aim to discover which color component is the topnotch for malaria parasites detection. In general, around 100 thick blood smear images have been tested in this study and the outcomes reveal that the best segmentation performance is segmentation through R component of RGB with 99.81% accuracy.
      5  28
  • Publication
    Image segmentation using k-means clustering and otsu's thresholding with classification method for human intestinal parasites
    ( 2020-07-09)
    Khairudin Norhanis Ayunie Ahmad
    ;
    Rohaizad Nurfatin Shamimi
    ;
    Aimi Salihah Abdul Nasir
    ;
    Lim Chee Chin
    ;
    Haryati Jaafar
    ;
    Mohamed Z.
    Helminth is one of the intestinal parasites that may cause harm and death to human. It is very important to have a system that is capable of assisting the technologist in investigating of fecal samples. In this paper, an automatic classification process is proposed to detect the different types of helminth eggs from fecal samples by using image processing technique. 50 samples of Ascaris Lumbricoides Ova (ALO) and Trichuris Trichiura Ova (TTO) are tested. First, these images undergo partial contrast stretching (PCS) technique to enhance the target images. Next, RGB and HSV color model have been compared in order to identify which color component is able to ease the segmentation process. S component shows a good results with high contrast between the target and the unwanted region. Then, Otsu's thresholding and k-means clustering are compared in order to to select the most suitable image processing method to be used in classification procedure. k-means clustering shows a better results compared to Otsu's thresholding. In classification process, area and size have been chosen as the feature to extract for the classification. The ratio for successfully detected ALO species is 84% while TTO is 76%.
      3  22
  • Publication
    Modified global and modified linear contrast stretching algorithms: new colour contrast enhancement techniques for microscopic analysis of Malaria slide images
    ( 2012-10-03)
    Aimi Salihah Abdul Nasir
    ;
    Mohd Yusoff Mashor
    ;
    Zeehaida Mohamed
    Malaria is one of the serious global health problem, causing widespread sufferings and deaths in various parts of the world. With the large number of cases diagnosed over the year, early detection and accurate diagnosis which facilitates prompt treatment is an essential requirement to control malaria. For centuries now, manual microscopic examination of blood slide remains the gold standard for malaria diagnosis. However, low contrast of the malaria and variable smears quality are some factors that may influence the accuracy of interpretation by microbiologists. In order to reduce this problem, this paper aims to investigate the performance of the proposed contrast enhancement techniques namely, modified global and modified linear contrast stretching as well as the conventional global and linear contrast stretching that have been applied on malaria images ofP. vivaxspecies. The results show that the proposed modified global and modified linear contrast stretching techniques have successfully increased the contrast of the parasites and the infected red blood cells compared to the conventional global and linear contrast stretching. Hence, the resultant images would become useful to microbiologists for identification of various stages and species of malaria.
      1  16
  • Publication
    Comparative analysis of conventional and modern high-rise hotels in Penang based on hourly simulation of cooling load performance using DesignBuilder
    (Semarak Ilmu Publishing, 2023)
    Muhammad Hafeez Abdul Nasir
    ;
    Ahmad Sanusi Hassan
    ;
    Aimi Salihah Abdul Nasir
    ;
    Mohd Suhaimi Mohd-Danuri
    ;
    Mohd Nasrun Mohd Nawi
    ;
    Rafikullah Deraman
    The study examines the energy efficiency performance of hotel façades in relation to the annual cooling load simulation. In achieving the objective, two case studies of high-rise city hotels are selected within the locality of Penang, Malaysia. The case studies are selected based on the year of construction coupled with the architectural styles encompassing conventional and modern design of hotel facades. In traditional hotel facades, passive design elements, including proper window and wall materials selection alongside window-to-wall ratio (WWR), are less significant. Comparatively, elements of passive design in modern hotel facades are notable. In assessing the thermal performance of the hotel façade, a case study of the conventional and modern high-rise city hotels in Penang are selected to undergo hourly cooling load simulation in the hotel guestroom using the DesignBuilder simulation program in establishing the hotel’s energy efficiency performance. The findings revealed the average annual cooling energy of the conventional and modern high-rise city hotel guestrooms is 553 kWh/m2 and 538 kWh/m2, respectively. The study concludes the elements of passive design, including WWR, window material selection, and external wall colour are crucial in determining energy-efficient hotel operations.
      17  1