Estimation of depth in stereo images using hybrid segmentation approaches

Priyank Y. Chauhan, K. Sharma
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Abstract

Segmentation is the process by which image is divided in to certain parts or regions in such a way that each part and region share a distinct property in common. This paper compare various segmentation approaches applicable to gray scale images. A comprehensive analysis has been done to choose best power and time efficient scheme from available state of art algorithms. SAD approach along with heuristic based segmentation as well as Fuzzy based clustering methods has been used for Depth estimation of stereo images. A case of selective blurring is also introduced that can be applied to remove undesired portion of images.
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基于混合分割方法的立体图像深度估计
分割是将图像分割成特定部分或区域的过程,这样每个部分和区域都有一个共同的独特属性。本文比较了适用于灰度图像的各种分割方法。从现有的最先进的算法中选择最佳的功率和时间效率方案进行了全面的分析。SAD方法与启发式分割和模糊聚类方法一起用于立体图像的深度估计。还介绍了一种选择性模糊的情况,可以应用于去除图像的不希望的部分。
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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