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首页> 外文期刊>Journal of ambient intelligence and humanized computing >Hardware implementation of fast bilateral filter and canny edge detector using Raspberry Pi for telemedicine applications
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Hardware implementation of fast bilateral filter and canny edge detector using Raspberry Pi for telemedicine applications

机译:快速双侧滤波器和罐头边缘检测器的硬件实现使用覆盆子PI进行远程医疗应用

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摘要

The role of preprocessing and segmentation are vital in image processing and computer vision. The medical images are prone to noise and the filtering algorithms are used for noise removal. In this paper, the fast bilateral filter is employed for noise removal and it has good edge preservation capacity. The segmentation algorithms are used to extract the region of interest and edge detection is a classical algorithm for tracing the contours of objects in an image. The canny edge detector is efficient when compared with the conventional edge detectors. The fast bilateral filter is proposed in this paper has the computation complexity of O(1) per pixel, while the classical bilateral filter has the computation complexity of O(W) operations per pixel, where W is the kernel size. The algorithms were implemented in Raspberry Pi using Open CV software package. The algorithms were tested on real time medical images.
机译:预处理和分割的作用在图像处理和计算机视觉中至关重要。 医学图像易于噪声,过滤算法用于噪声去除。 在本文中,使用快速双侧过滤器用于噪音,并且具有良好的边缘保存容量。 分割算法用于提取感兴趣区域和边缘检测是一种用于跟踪图像中对象的轮廓的经典算法。 与传统边缘检测器相比,罐头边缘检测器是有效的。 本文提出了快速双侧滤波器的计算复杂性O(1)每像素,而经典双侧滤波器具有每个像素的O(W)操作的计算复杂性,其中W是内核大小。 使用Open CV软件包在Raspberry PI中实现算法。 在实时医学图像测试算法。

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