Unsupervised image segmentation using lab color space

Erum Fida, Junaid Baber, Maheen Bakhtyar, Rabia Fida, Muhammad Javid Iqbal
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引用次数: 2

Abstract

Image segmentation helps computer to understand visual information. A number of techniques are proposed for image segmentation that are either interactive or automatic. Interactive techniques provide satisfactory result but user interaction is the biggest limitation when large number of images are considered. On the other hand automatic image segmentation is difficult to acquire satisfactory results. We propose an unsupervised approach for automatic image segmentation that employ image color information to segment an image into foreground and background. The results confirm the effectiveness of the approach.
使用实验室色彩空间的无监督图像分割
图像分割有助于计算机理解视觉信息。提出了许多交互式或自动的图像分割技术。交互技术提供了令人满意的结果,但当考虑大量图像时,用户交互是最大的限制。另一方面,自动图像分割难以获得满意的结果。我们提出了一种无监督的图像自动分割方法,该方法利用图像颜色信息将图像分割为前景和背景。结果证实了该方法的有效性。
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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