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  1. 1

    Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications by Teo, Chee Huat

    Published 2016
    “…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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    Thesis
  2. 2

    Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

    Published 2007
    “…In this research, a vision system algorithm has been developed to identify and locate base of young corn trees based upon robot vision technology, pattern recognition techniques, and knowledge-based decision theory. …”
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    Thesis
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    Vision Based Calibration and Localization Technique for Video Sensor Networks by Mohamed Sharif, Sharif Amar Mohamed Sharif

    Published 2009
    “…Very few of these localization algorithms use vision based technique. In this work, a vision based technique is proposed for localizing and configuring the camera nodes in video wireless sensor networks. …”
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    Thesis
  5. 5

    Stereo vision for visual object tracking and distance measurement assessment / Sukarnur Che Abdulla...[et al.] by Che Abdullah, Sukarnur, Amari, Mohamad Dzulhelmy, Ohka, Masahiro

    Published 2019
    “…Furthermore, the project proposes a new program algorithm for binocular vision system to work, in order to identify distance of an object with a basic equation has been derived and set in the designed algorithm. …”
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    Article
  6. 6

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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    Thesis
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    i-ManGoeS by Ahmad, Khairul Adilah, Abdul Malik, Anis Faradella

    Published 2017
    “…At the end this paper give some preliminary results and conclude on the effectiveness of this approach. i-ManGoes is an application software that use computer vision technique to classify the children activity and satisfaction base on gesture. …”
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    Book Section
  9. 9

    Design and Development of a Vision System Interface for Three Degree of Freedom Agricultural Robot by Omrane, Bouketir

    Published 1999
    “…The recognition process was achieved by using C++ programming language enhanced by MIL functions. An algorithm based on empirical results was developed in order to convert the target coordinates from the image plane (pixel) into the robot plane (cm). …”
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    Thesis
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    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
  12. 12

    Face Detection System / Chan Beh Teng by Chan, Beh Teng

    Published 2004
    “…The Face Detection System is implemented in visual Basic 6.0 The system was developed based on the Unified Process,which uses object-oriented paradigm as the basis of software development.…”
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    Thesis
  13. 13

    Building a feature-space for visual surveillance by Altahir, A.A., Asirvadam, V.S.

    Published 2014
    “…The future of visual surveillance applications relies on the developments in the area of computer vision, human motion analysis and computer algorithms. …”
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    Conference or Workshop Item
  14. 14

    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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    Thesis
  15. 15

    Classification of herbs plant diseases via hierarchical dynamic artificial neural network by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

    Published 2010
    “…A key point in the implementation of optimal classifiers is the selection of features that characterize the image. Basically, in this study, image processing and pattern classification are going to be used to implement a machine vision system that could identify and classify the visual symptoms of herb plants diseases. …”
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    Article
  16. 16

    Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

    Published 2011
    “…A key point in the implementation of optimal classifiers is the selection of features that characterize the image. Basically, in this study, image processing and pattern classification are going to be used to implement a machine vision system that could identify and classify the visual symptoms of herb plants diseases. …”
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    Article
  17. 17

    Review of deep convolution neural network in image classification by Al-Saffar, Ahmed Ali Mohammed, Tao, Hai, Mohammed, Ahmed Talab

    Published 2017
    “…The convolution neural network model trained by the deep learning algorithm has made remarkable achievements in many large-scale identification tasks in the field of computer vision since its introduction. …”
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    Article
  18. 18

    Satellite Image Segmentation Using Thresholding Technique by Khalik, Mohd Haffez

    Published 2017
    “…Image segmentation is one of the basic techniques of image processing and computer vision. …”
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    Thesis
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    A Novel Method for Fashion Clothing Image Classification Based on Deep Learning by Yoon Shin, Seong, Jo, Gwanghyun, Wang, Guangxing

    Published 2023
    “…This paper suggested a deep learning-based image classification technique based on a CNN model and improved convolutional and pooling layers. …”
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    Article
  20. 20

    A Review on the Development of Indonesian Sign Language Recognition System by Jasni, Mohamad Zain, Sutarman, na, Mazlina, Abdul Majid

    Published 2013
    “…Sign language recognition basically uses two approaches: (1) computer vision-based gesture recognition, in which a camera is used as input and videos are captured in the form of video files stored before being processed using image processing; (2) approach based on sensor data, which is done by using a series of sensors that are integrated with gloves to get the motion features finger grooves and hand movements. …”
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    Article