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IMAGE GRADIENT SEGMENTATION (SHADING, PROCESSING, ANALYSIS).

机译:图像梯度分割(着色,处理,分析)。

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摘要

In this thesis we describe an approach to identification of shaded segments in an image providing a model for the curved surface that generated the segment. The analysis, development, implementation, and evaluation of an algorithm that obtains the segments are explained. The output of the algorithm is a list of the image segments where shading was identified along with the geometric and curved surface model parameters of each segment.;The Image Gradient Segmentation Algorithm includes three phases: (1) Partition of the BxBy map into components with curved surface models, (2) Segmentation of the image into connected regions corresponding to the BxBy map partitions, and (3) Identification of curved surface models. The algorithm has been implemented in a stand-alone microprocessor-based system. Examples of Image Gradient Segmentation are provided for synthesized as well as real things.;The algorithm provides a description of images in terms of components which correspond to curved surfaces in scenes. Examples described here demonstrate the feasibility and reliability of the algorithm. Future work will consider the integration of this image description into systems which interpret more general scenes.;The Image Gradient (BxBy) map, a two-dimensional plot of the distribution of image points in the image gradient space, is utilized as a tool in the development of the algorithm. Properties of the surface gradient and image gradient maps for curved surface models are analyzed. The BxBy map is affected by noise in the image, and detailed analysis of the effects of noise in the image gradient space is presented. The noise analysis is used in the development of the algorithm.
机译:在本文中,我们描述了一种识别图像中阴影部分的方法,该方法为生成该部分的曲面提供了模型。解释了获得分段的算法的分析,开发,实现和评估。该算法的输出是一列图像片段,其中识别出阴影以及每个片段的几何和曲面模型参数。图像梯度分割算法包括三个阶段:(1)将BxBy映射分为多个分量曲面模型;(2)将图像分割为对应于BxBy映射分区的连接区域;以及(3)曲面模型的识别。该算法已在独立的基于微处理器的系统中实现。提供了图像梯度分割的示例,以用于合成物体和真实物体。;该算法根据与场景中曲面相对应的分量对图像进行了描述。这里描述的示例证明了该算法的可行性和可靠性。未来的工作将考虑将该图像描述集成到解释更一般场景的系统中。图像梯度(BxBy)图是图像梯度空间中图像点分布的二维图,被用作工具。算法的发展。分析了曲面模型的表面梯度和图像梯度图的属性。 BxBy贴图受图像中噪声的影响,并详细分析了图像梯度空间中噪声的影响。噪声分析用于算法的开发中。

著录项

  • 作者

    BRACHO, RAFAEL.;

  • 作者单位

    Carnegie Mellon University.;

  • 授予单位 Carnegie Mellon University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 1984
  • 页码 138 p.
  • 总页数 138
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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