Optimized fuzzy cellular automata for synthetic aperture radar image edge detection

Farbod, Mohammad; Akbarizadeh, Gholamreza; Kosarian, Abdolnabi; Rangzan, Kazem

doi:10.1117/1.jei.27.1.013030

Cited by 41 publications

(15 citation statements)

References 38 publications

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“…G. Akbarizadeh et al [38] proposed a curvelet and watershed-based method for segmentation of SAR images and recognition of various textures in them, and curvelet is an effective method for noise reduction and extracting useful features. And Farbod et al [42] proposed an optimized fuzzy cellular automata algorithm for SAR image edge detection. Fang et al [43] detected flow noise of gas-liquid two-phase flow in horizontal pipeline by using the acoustic emission technique, and processed signals by wavelet transform and chaotic analysis.…”

Section: Theoretical Analysismentioning

confidence: 99%

Measurement of interphase forces based on dual-modality ERT/DP sensor in horizontal two-phase flow gas-water

et al. 2019

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In order to better understand the mechanisms of two-phase flow and the prevailing flow regimes in horizontal pipelines, the evaluation of interphase forces is paramount. This study develops a method to quantitatively estimate the interphase force in two-phase gas-water flow in horizontal pipeline. The electrical resistance tomography technology is used to measure the void fraction, while the differential pressure perpendicular to the horizontal pipe is measured in different flow patterns via a Differential Pressure sensor. The inner pipe diameter is 50 mm, the water flow range from 3.26 m 3 /h to 7.36 m 3 /h, the gas flow rate range from 1 to 60 l/min, which covered a range of flow patterns, the absolute pressure range from 0.07 MPa to 0.12 MPa. The relationship between the differential pressure drop and interphase force is established, and the effects of these forces on the flow are analyzed. Experimental results indicate that the dual-modality measurement system was successfully provided a quantitative evaluation of interphase forces in two-phase horizontal gas-water flow.

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Section: Theoretical Analysismentioning

confidence: 99%

Measurement of interphase forces based on dual-modality ERT/DP sensor in horizontal two-phase flow gas-water

et al. 2019

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“…It is important de mention that there are other approaches pursued to extract edges combining cellular automata and fuzzy rules [21] or local spectral histogram (LSH) [22] which are mainly applied on Synthetic Aperture Radar (SAR) images but that can be adapted to LV images' segmentation due to the high degree of accuracy in contour delineation and noise processing.…”

Section: Introductionmentioning

confidence: 99%

Left ventricular segmentation based on a parallel watershed transformation towards an accurate heart function evaluation

Mahmoudi

Ameur

Ammari

et al. 2020

IET Image Processing

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Magnetic Resonance Imaging (MRI) has emerged as the golden reference for cardiac examination. This modality allows the assessment of human cardiovascular morphology, functioning, and perfusion. Although a couple of challenging issues, such as the cardiac MR image's features and the large variability of images among several patients, still influences the cardiac cavities' segmentation and needs to be carried out. In this paper, we have profoundly reviewed and fully compared semi-automated segmentation methods performed on cardiac Cine-MR short-axis images for the evaluation of the left ventricular functions. However, the number of parameters handled by the synthesized works is limited if not null. For the sake of ensuring the highest coverage of the LV parameters computing, we have introduced a parallel watershedbased approach to segment the left ventricular allowing hence the computation of six parameters (End-Diastolic Volume, End-Systolic Volume, Ejection Fraction, Cardiac output, Stroke Volume and Left Ventricular Mass). An algorithm is associated with main considered measurements. The experimental results that were obtained through studying twenty patients' MRI data base, demonstrate the accuracy of our approach for estimating real values of the maximal set of parameters thanks to a faithful segmentation of the myocardium.

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“…This type of sensor is able to operate far away from potential targets and functions during the daytime as well as nighttime, under all weather conditions. In particular, SAR Image Segmentation (SIS) techniques [10][11][12] can segment humans from other components (e.g. objects, background) in the scene.…”

Section: Introductionmentioning

confidence: 99%

Learning to recognise 3D human action from a new skeleton‐based representation using deep convolutional neural networks

Pham

Khoudour

Crouzil

et al. 2019

IET Computer Vision

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Recognizing human actions in untrimmed videos is an important challenging task. An effective 3D motion representation and a powerful learning model are two key factors influencing recognition performance. In this paper we introduce a new skeletonbased representation for 3D action recognition in videos. The key idea of the proposed representation is to transform 3D joint coordinates of the human body carried in skeleton sequences into RGB images via a color encoding process. By normalizing the 3D joint coordinates and dividing each skeleton frame into five parts, where the joints are concatenated according to the order of their physical connections, the color-coded representation is able to represent spatio-temporal evolutions of complex 3D motions, independently of the length of each sequence. We then design and train different Deep Convolutional Neural Networks (D-CNNs) based on the Residual Network architecture (ResNet) on the obtained image-based representations to learn 3D motion features and classify them into classes. Our method is evaluated on two widely used action recognition benchmarks: MSR Action3D and NTU-RGB+D, a very large-scale dataset for 3D human action recognition. The experimental results demonstrate that the proposed method outperforms previous state-of-the-art approaches whilst requiring less computation for training and prediction.

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Optimized fuzzy cellular automata for synthetic aperture radar image edge detection

Cited by 41 publications

References 38 publications

Measurement of interphase forces based on dual-modality ERT/DP sensor in horizontal two-phase flow gas-water

Measurement of interphase forces based on dual-modality ERT/DP sensor in horizontal two-phase flow gas-water

Left ventricular segmentation based on a parallel watershed transformation towards an accurate heart function evaluation

Learning to recognise 3D human action from a new skeleton‐based representation using deep convolutional neural networks

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