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A New Proposed Method for Image Segmentation Based on Gray Scale Morphological Transformations

机译:一种新的基于灰度形态学变换的图像分割方法

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Image segmentation is one of the most important steps leading to the analysis of processed data. Its main goal is to divide an Image into parts that have a strong correlation with Areas of the Real world contained in the Image .Image Segmentation by Mathematical Morphology is a Methodology based upon the notions of Reconstruction and Gradient method of an Image. Reconstruction is a very useful operator for Image Filtering, Segmentation, and Feature Extraction. In this paper a new Method is proposed based on the notion of regional maxima and makes use of Sequential reconstruction algorithm and Morphological Gradient .The present paper has two main sections, first is reconstruction of original Image from blurred Image by eliminating noise. Second is segment the Image by applying Morphological gradient method this method produced good result over conventional methods.
机译:图像分割是导致对已处理数据进行分析的最重要步骤之一。它的主要目标是将图像划分为与图像中包含的现实世界的区域密切相关的部分。数学形态学的图像分割是一种基于图像的重构和渐变方法的方法。重建对于图像过滤,分割和特征提取而言是非常有用的运算符。本文提出了一种基于区域最大值的概念的新方法,该方法利用了顺序重构算法和形态学梯度。本文主要分为两个部分,首先是通过消除噪声从模糊图像中重构原始图像。其次是通过应用形态学梯度法对图像进行分割,与常规方法相比,该方法取得了很好的效果。

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