基于积分图像的自适应阈值分割

D. Bradley, G. Roth
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引用次数: 1063

摘要

在许多计算机视觉和图形应用中,图像阈值分割是一项常见的任务。阈值化图像的目的是将像素分类为“暗”或“亮”。自适应阈值法是一种考虑光照空间变化的阈值法。我们提出了一种利用输入的积分图像进行实时自适应阈值分割的技术。我们的技术是以前一种方法的扩展。然而,我们的解决方案对图像中光照变化的鲁棒性更强。此外,我们的方法简单且易于实现。我们的技术适用于以实时帧率处理实时视频流,使其成为增强现实等交互式应用的宝贵工具。源代码可在线获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Thresholding using the Integral Image
Image thresholding is a common task in many computer vision and graphics applications. The goal of thresholding an image is to classify pixels as either "dark" or "light." Adaptive thresholding is a form of thresholding that takes into account spatial variations in illumination. We present a technique for real-time adaptive thresholding using the integral image of the input. Our technique is an extension of a previous method. However, our solution is more robust to illumination changes in the image. Additionally, our method is simple and easy to implement. Our technique is suitable for processing live video streams at a real-time frame-rate, making it a valuable tool for interactive applications such as augmented reality. Source code is available online.
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