Big data simulation for surface reconstruction on CPU-GPU platform

Afrouzi, Hadi Nabipour

doi:10.1088/1742-6596/1192/1/012006

Cited by 2 publications

(2 citation statements)

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“…where the G x is the gradient changes in the horizontal direction, G y is the gradient changes in the vertical direction. When the G x and G y are combined, it produces the gradient magnitude as in (3) and the gradient direction as in (4).…”

Section: Image Segmentationmentioning

confidence: 99%

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Performance of CPU GPU Parallel Architecture on Segmentation and Geometrical Features Extraction of Malaysian Herb Leaves

Hadi¹,

HALIM²,

Lazim³

et al. 2022

Malaysian J. Math. Sci.

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Image recognition includes the segmentation of image boundary geometrical features extraction and classification is used in the particular image database development. The ultimate challenge in this task is it is computationally expensive. This paper highlighted a CPU GPU architecture for image segmentation and features extraction processes of 125 images of Malaysian Herb Leaves. Two GPUs and three kernels are utilized in the CPU GPU platform using MATLAB software. Each of herb image has pixel dimensions 16161080. The segmentation process uses the Sobel operator which is then used to extract the boundary points. Finally seven geometrical features are extracted for each image. Both processes are first executed on the CPU alone before bringing it onto a CPU GPU platform to accelerate the computational performance. The results show that the developed CPU GPU platform has accelerated the computation process by a factor of 4.13. However the efficiency shows a decline which suggests that the processors utilization must be improved in the future to balance the load distribution.

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Section: Image Segmentationmentioning

confidence: 99%

“…The number of kernels depends on the need of the whole process. Some existing work use only one kernel, for example, in denoising 3D point cloud [5], and some use several kernels such as in extracting surface points [4].…”

Section: Introductionmentioning

confidence: 99%