A parallel approach for region-growing segmentation

A. Baby, K. Balachandran
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引用次数: 9

Abstract

Image Segmentations play a heavy role in areas such as computer vision and image processing due to its broad usage and immense applications. Because of the large importance of image segmentation a number of algorithms have been proposed and different approaches have been adopted. In this theme I tried to parallelize the image segmentation using a region growing algorithm. The primary goal behind this theme is to enhance performance or speed up the image segmentation on large volume image data sets, i.e. Very high resolution images (VHR). In parliamentary law to get the full advantage of GPU computing, equally spread the workload among the available threads. Threads assigned to individual pixels iteratively merge with adjacent segments and always ensuring the standards that the heterogeneity of image objects should be belittled. An experimental analysis upon different orbital sensor images has made out in order to assess the quality of results.
区域增长分割的并行方法
图像分割由于其广泛的用途和巨大的应用,在计算机视觉和图像处理等领域发挥着重要的作用。由于图像分割的重要性,已经提出了许多算法,并采用了不同的方法。在这个主题中,我尝试使用区域增长算法并行化图像分割。该主题的主要目标是提高大容量图像数据集(即甚高分辨率图像(VHR))上的图像分割性能或速度。在议会法中,为了充分利用GPU计算的优势,将工作负载均匀地分布在可用的线程之间。分配给单个像素的线程迭代地与相邻的段合并,并始终确保图像对象的异构性应该被低估的标准。对不同的轨道传感器图像进行了实验分析,以评价结果的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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