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Formulation of hybrid 3D image segmentation algorithm based partial differential equation
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Proceeding Paper -
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Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
Published 2011“…Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. …”
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Thesis -
3
Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset
Published 2018“…Both methods are able to speed up the segmentation time. …”
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Monograph -
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Multiregion segmentation of mammogram images by using parametric kernel graph cut algorithm / Nurhanani Abdul Rahim, Nor Farah Nabilah Mushtafa and Nadhirah Afiqah Zailan
Published 2019“…Therefore, Parametric Kernel Graph Cut Algorithm had proved its ability to segment the microcalcification robustly and efficiently.…”
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Student Project -
5
Segmentation of Magnetic Resonance Brain Images Using Watershed Algorithm
Published 2004“…The watershed segmentation algorithm is a very powerful segmentation tool, but it also has difficulty in segmenting MR images due to noise and shading effect present. …”
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Image segmentation based on normalised cuts with clustering algorithm
Published 2013“…This research presents an image segmentation approach based on normalised cuts. Normalised cuts based image segmentation is well known for its reliability to produce good segmentation. …”
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A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm
Published 2024journal::journal article -
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Noise is one of the obstacles for brain MRI segmentation. The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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9
Customer segmentation using clustering techniques / Mohamad Amir Salihin Mustafa
Published 2024“…Studying clustering methodologies, creating a K-Means clustering model, and assessing its quality for efficient client segmentation are the main goals. …”
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10
Disparity map algorithm using hierarchical of bitwise pixel differences and segment-tree from stereo image
Published 2024“…The algorithm development can be categorized into local, global, and semi-global methods. …”
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Thesis -
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Based on previous researches, most existing segmentation methods focused on a specific environment. …”
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Thesis -
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Image clustering comparison of two color segmentation techniques
Published 2010“…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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13
Computer-aided acute leukemia blast cells segmentation in peripheral blood images
Published 2015“…The quantitative evaluation reveals that the proposed method obtain a better segmentation performance compared with its counterparts and achieves remarkable segmentation results of approximately 96 % in blast cell extraction and 94 % in nucleus/cytoplasm separation.…”
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Article -
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Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images
Published 2022“…The findings revealed that the algorithm outperformed the other active contour-based approaches in computational time and segmentation accuracy. …”
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Article -
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Identify texture of MRI human brain using Adaptive Fuzzy C-Means (AFCM) Algorithm / Faridatul Akma Mohd Noor
Published 2010“…The result of this research can be uses for segmentation and classification process. To access its viability, a prototype with interactive graphical user interface (GUI) was developed and tested for its reliability. …”
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Thesis -
16
Segmentation of MRI Prostate Images using Gaussian Mixture Models (GMMs)
Published 2016“…This method is also compared to K-Means algorithm to evaluate its performance with synthetic image and also clinical MRI image.…”
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Final Year Project -
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A rule-based segmentation method for fruit images under natural illumination
Published 2014“…This is due to the existence of non-uniform illumination on the object surface.Technically, different illuminations lead to different intensity on the object surface colour.This condition leads to low quality segmented images and therefore reduces the accuracy of object classification.Image segmentation can be accomplished using several methods such as Otsu, K-means and Fuzzy C-means.However, these three traditional methods have limitations in producing accurate segmented areas due to the existence of illumination on the object surface.Therefore, this paper developed a rule-based segmentation method that is able to segment natural images correctly and accurately.This method uses IF-THEN algorithm to segment the images of interest object. …”
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Conference or Workshop Item -
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Infrared Image Enhancement and Segmentation for Extracting the Thermal Anomalies in Electrical Equipment
Published 2012“…Experimental results through different segmentation algorithms show that by enhancing the infrared image using the proposed algorithm could improve the segmentation performance. …”
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Article -
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Curvelet based automatic segmentation of supraspinatus tendon from ultrasound image: A focused assistive diagnostic method
Published 2014“…Methods: The automatic segmentation of SSP tendon ultrasound image was performed to provide focused and more accurate diagnosis. …”
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