Search Results - (( program segmentation using algorithm ) OR ( post segmentation using algorithm ))

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  1. 1

    Development Of Semi-Automatic Liver Segmentation Method For Three-Dimensional Computed Tomography Dataset by Chiang, Yi Fan

    Published 2017
    “…The liver segmentation program with proposed algorithm is evaluated with CT datasets obtained from SLIVER07 to prove its effectiveness in liver segmentation. …”
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    Monograph
  2. 2

    Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images by Ali Hussein Aboali, Maged Yahya

    Published 2018
    “…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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    Thesis
  3. 3

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…The Gaussian Mixture Model (GMM) is a clustering algorithm that is commonly used for brain MRI segmentation. …”
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    Thesis
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    Stereo matching algorithm using census transform and segment tree for depth estimation by Hamzah, Rostam Affendi, Zainal Azali, Muhammad Nazmi, Mohd Noh, Zarina, Tengku Wook, Tg Mohd Faisal, Zainal Abidin, Izwan

    Published 2023
    “…Fundamentally, the framework input is the stereo image which represents left and right images respectively. The proposed algorithm in this article has four steps in total, which starts with the matching cost computation using census transform, cost aggregation utilizes segment-tree, optimization using winner-takes-all (WTA) strategy, and post-processing stage uses weighted median filter. …”
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    Article
  6. 6

    Human body electromagnetic radiation: the physiological characteristic for post stroke patients / Ros Shilawani S. Abdul Kadir by S. Abdul Kadir, Ros Shilawani

    Published 2018
    “…This finding confirmed that the EMR of human body has different characteristics between samples of post stroke and non-stroke and between their body segments.…”
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    Thesis
  7. 7

    Drone Based Image Processing For Precision Agriculture by Sharif, Muhammad Arif Syafiq Md

    Published 2019
    “…Post K-means clustering, the diseased portions of the plants were assessed using Hue-Saturation-Value (HSV) based image segmentation algorithm. …”
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    Monograph
  8. 8

    Moment-based extraction on handwritten digits by Taliba, Jumail, Shamsuddin, Siti Mariyam, Tan, Shuen Chuan

    Published 2005
    “…Classification and recognition results are analyzed to determine the necessity of operation thinning when dealing with the moment functions. A Simple Block Segmentation with Moore Tracing Algorithm (SBS & MNTA) is used in image segmentation while Safe-point Thinning Algorithm (SPTA) is applied in image thinning process. …”
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    Monograph
  9. 9

    Spectral texture segmentation of Magnetic Resonance Imaging (MRI) brain images for glioma brain tumour detection / Rosniza Roslan by Roslan, Rosniza

    Published 2013
    “…Experiments conducted on 64 MRI images, of all sequences showed that texture energy is the best texture feature to be used in glioma segmentation. Fuzzy C-Means clustering algorithm is then used to segment texture energy features from 126 MRI brain images of all sequences. …”
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    Thesis
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    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

    Published 2005
    “…The project used Back-propagation Neural Network for the algorithm to classified images. …”
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    Thesis
  13. 13

    Word segmentation of output response for sign language devices by Za'bah, Nor Farahidah, Muhammad Nazmi, Ahmad Amierul Asyraf, Azman, Amelia Wong

    Published 2020
    “…The proposed text segmentation method in this work is by using the dynamic programming and back-off algorithm, together with the probability score using word matching with an English language text corpus. …”
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    Article
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    Interactive blood vessel segmentation from retinal fundus image based on canny edge detector by Ibrahim, Haidi, Ooi, Alexander Ze Hwan, Soo, Siang Teoh, Embong, Zunaina, Abd Hamid, Aini Ismafairus, Zainon, Rafidah, Shir, Li Wang, Theam, Foo Ng, Hamzah, Rostam Affendi

    Published 2021
    “…The program will draw out the vessel edges. After that, those vessel edges will be segmented to bring focus on its details or detect the abnormal vessel. …”
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    Article
  16. 16

    Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging by Norhasmira, Mohammad, Anuar Mikdad, Muad, Rohana, Ahmad, Mohd Yusmiaidil, Putera Mohd Yusof

    Published 2022
    “…Results: Image segmentation using the DP-AC algorithm enhanced the visibility of the image features in the region of interest while suppressing the image’s background noise. …”
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    Article
  17. 17

    An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery by Aisyah Marliza Muhmad Kamarulzaman, Wan Shafrina Wan Mohd Jaafar, Siti Nor Maizah Saad, Hamdan Omar, Mohd. Rizaludin Mahmud

    Published 2021
    “…This research implemented a technique for detecting, segmenting, classifying, and measuring tree stumps by using the Multiresolution Segmentation Algorithm method. …”
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    Article
  18. 18

    Fast recovery of unknown coefficients in DCT-transformed images by Ong, Sim Ying, Li, Shujun, Wong, Kok Sheik, Tan, Kuan Yew

    Published 2017
    “…In this paper, we propose a fast hierarchical DCT coefficients recovery method by combining image segmentation and linear programming. In theory the proposed method can reduce the overall time complexity by a linear factor which is the number of image segments used. …”
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    Article
  19. 19

    Extracting oil palm crown from worldview-2 satellite image by Alexius Korom, Phua, Mui How, Y. Hirata, T. Matsuura

    Published 2014
    “…This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. …”
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    Conference or Workshop Item
  20. 20

    STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

    Published 2021
    “…A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
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    Article