Visual ball tracking and prediction with unique segmented area on soccer robot

Setiawardhana,; Dikairono, Rudy; Sardjono, Tri Arief; Purwanto, Djoko

doi:10.1109/isitia.2017.8124110

Cited by 12 publications

(6 citation statements)

References 9 publications

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“…Posisi gawang menggunakan segmentasi berbasis warna dan ekstraksi fitur telah diperkenalkan di Fitriana et al dan Setiawardhana dkk. [4], [5]. Selanjutnya, berbagai metode telah diusulkan untuk lokalisasi robot sepakbola beroda.…”

Section: Pendahuluanunclassified

Navigasi Robot Sepak Bola Beroda Menggunakan Particle Filter Localization

et al. 2022

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"Dimana saya?" adalah pertanyaan utama, yang merupakan representasi lokalisasi atau penentuan psisi, dimana hal tersebut adalah permasalahan yang harus dijawab oleh robot sepak bola beroda. Deadreconing adalah metode paling populer yang digunakan dalam pergerakan robot beroda. Namun, kesalahan posisi yang meningkat adalah topik utama dari metode deadreconing. Selanjutnya dalam makalah ini diusulkan lokalisasi sepak bola beroda menggunakan filter partikel melalui Omnivision. Model sensor dan model gerak dari filter partikel juga dibahas, dimana model sensor diperoleh dari segmentasi dan ekstraksi ciri landmark lapangan sepak bola. Hasil eksperimen menunjukkan bahwa metode yang diusulkan memperkirakan posisi robot secara akurat dengan kesalahan 15%.

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Section: Pendahuluanunclassified

Navigasi Robot Sepak Bola Beroda Menggunakan Particle Filter Localization

et al. 2022

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“…The closing operation aims to smooth the contours of the object and fill the small holes with the elements of the matrix structure. [9] Image of threshold result of HSV will be done opening and closing process. The opening is a process of erosion and then dilation, and closing is a process of dilation then erosion.…”

Section: E Morphologicalmentioning

confidence: 99%

Object Detection of Omnidirectional Vision Using PSO-Neural Network for Soccer Robot

Setyawan¹,

Mardiyah²,

Hidayat³

et al. 2018

EECSI

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The vision system in soccer robot is needed to recognize the object around the robot environment. Omnidirectional vision system has been widely developed to find the object such as a ball, goalpost, and the white line in a field and recognized the distance and an angle between the object and robot. The most challenging in develop Omni-vision system is image distortion resulting from spherical mirror or lenses. This paper presents an efficient Omni-vision system using spherical lenses for real-time object detection. Aiming to overcome the image distortion and computation complexity, the distance calculation between object and robot from the spherical image is modeled using the neural network with optimized by particle swarm optimization. The experimental result shows the effectiveness of our development in the term of accuracy and processing time.

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“…, and derivatives of the logarithmized colour channels have been proposed in literature [33]. In general, the HSV colour transformation proves to be insensitive to shadow, shading, and specular edges [33] and has been used in different applications such as object segmentation [34], detection [35], tracking [36], and recognition in the images [37]. More details about HSV colour transformation can be found in [38].…”

Section: Colour Space Transformation Many Photometric Invariants Sucmentioning

confidence: 99%

Unsupervised Change Detection in Landsat Images with Atmospheric Artifacts: A Fuzzy Multiobjective Approach

Kusetoğulları

Yavariabdi

2018

Mathematical Problems in Engineering

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A new unsupervised approach based on a hybrid wavelet transform and Fuzzy Clustering Method (FCM) with Multiobjective Particle Swarm Optimization (MO-PSO) is proposed to obtain a binary change mask in Landsat images acquired with different atmospheric conditions. The proposed method uses the following steps: (1) preprocessing, (2) classification of preprocessed image, and (3) binary masks fusion. Firstly, a photometric invariant technique is used to transform the Landsat images from RGB to HSV colour space. A hybrid wavelet transform based on Stationary (SWT) and Discrete Wavelet (DWT) Transforms is applied to the hue channel of two Landsat satellite images to create subbands. After that, mean shift clustering method is applied to the subband difference images, computed using the absolute-valued difference technique, to smooth the difference images. Then, the proposed method optimizes iteratively two different fuzzy based objective functions using MO-PSO to evaluate changed and unchanged regions of the smoothed difference images separately. Finally, a fusion approach based on connected component with union technique is proposed to fuse two binary masks to estimate the final solution. Experimental results show the robustness of the proposed method to existence of haze and thin clouds as well as Gaussian noise in Landsat images.

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Visual ball tracking and prediction with unique segmented area on soccer robot

Cited by 12 publications

References 9 publications

Navigasi Robot Sepak Bola Beroda Menggunakan Particle Filter Localization

Navigasi Robot Sepak Bola Beroda Menggunakan Particle Filter Localization

Object Detection of Omnidirectional Vision Using PSO-Neural Network for Soccer Robot

Unsupervised Change Detection in Landsat Images with Atmospheric Artifacts: A Fuzzy Multiobjective Approach

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