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An image texture insensitive method for saliency detection

机译:一种图像纹理不敏感的显着性检测方法

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摘要

We propose a texture insensitive, region based image saliency detection algorithm, having excellent detection and localization properties, to obtain salient objects. We use a total variation based regularizer to suppress textures from the image and to make the method invariant to textural variations in the scene. This leads to an image that contains piecewise constant gray valued regions. This texture-free image is sparsely segmented into a small number of regions using the expectation maximization algorithm assuming a Gaussian mixture model. We compute three different saliency measures for every region using its intensity and spatial features. We adopt a relevance feedback mechanism to obtain weights for combining the three saliency measures and obtain the final saliency map. Next we input the thres-holded saliency map to an image matting technique and extract the salient objects from the image with exact boundaries. Experimental comparisons with existing saliency detection algorithms demonstrate the superiority of the proposed technique. (C) 2017 Elsevier Inc. All rights reserved.
机译:我们提出了一种纹理不敏感的,基于区域的图像显着性检测算法,该算法具有出色的检测和定位特性,可以获得显着的目标。我们使用基于总变化量的正则化器来抑制图像中的纹理并使该方法对于场景中的纹理变化不变。这导致包含分段恒定灰度值区域的图像。假设高斯混合模型,使用期望最大化算法将此无纹理图像稀疏地分割为少量区域。我们使用其强度和空间特征为每个区域计算三种不同的显着性度量。我们采用相关性反馈机制来获得将三种显着性度量结合起来的权重,并获得最终显着性图。接下来,将阈值显着性图输入到图像消光技术中,并从图像中提取具有精确边界的显着对象。与现有显着性检测算法的实验比较证明了所提出技术的优越性。 (C)2017 Elsevier Inc.保留所有权利。

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