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Image segmentation using a texture gradient based watershed transform

机译:使用基于纹理梯度的分水岭变换进行图像分割

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The segmentation of images into meaningful and homogenous regions is a key method for image analysis within applications such as content based retrieval. The watershed transform is a well established tool for the segmentation of images. However, watershed segmentation is often not effective for textured image regions that are perceptually homogeneous. In order to segment such regions properly, the concept of the "texture gradient" is introduced. Texture information and its gradient are extracted using a novel nondecimated form of a complex wavelet transform. A novel marker location algorithm is subsequently used to locate significant homogeneous textured or non textured regions. A marker driven watershed transform is then used to segment the identified regions properly. The combined algorithm produces effective texture and intensity based segmentation for application to content based image retrieval.
机译:将图像分割为有意义的同质区域是在诸如基于内容的检索之类的应用程序中进行图像分析的关键方法。分水岭变换是一种很好的图像分割工具。但是,分水岭分割对于感知上均匀的纹理图像区域通常无效。为了适当地分割这些区域,引入了“纹理梯度”的概念。纹理信息及其梯度是使用复杂小波变换的新颖非抽取形式提取的。随后使用新颖的标记定位算法来定位明显的均匀纹理或非纹理区域。然后使用标记驱动的分水岭变换来正确分割已识别的区域。组合算法产生有效的基于纹理和强度的分割,以应用于基于内容的图像检索。

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