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Extraction of Salient Region Based on Visual Perception

机译:基于视觉感知的显着区域提取

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摘要

In order to better analysis and understand digital images, a salient region extraction algorithm based on visual perception is proposed. First, a multi-scale difference of gaussian filter is used to the image, which simulates the center-peripheral response of the human visual nerve cell; Then, we use the pulse cosine transform to extract the edge information of the image, simulate the side inhibition process of the nerve cell, and obtain the image feature maps at different scales. Finally, the threshold segmentation and regional expansion of the feature graph are used to construct the focal window in the region with the most prominent image features. The experiment was performed on 500 images of the salient object database provided by Microsoft Research Asia (MSRA) using the proposed method, take β~2 = 0.3, the value of F-measure is as high as 0.816. Results show that the method can be effectively to extract salient area of the image with different content, different target location and size, and has the location and size on the adaptability.
机译:为了更好地分析和理解数字图像,提出了一种基于视觉的显着区域提取算法。首先,对图像使用多尺度差分高斯滤波器,以模拟人类视觉神经细胞的中心周围反应。然后,我们使用脉冲余弦变换提取图像的边缘信息,模拟神经细胞的侧面抑制过程,并获得不同比例的图像特征图。最后,特征图的阈值分割和区域扩展被用于在图像特征最突出的区域中构造焦点窗口。使用所提出的方法对Microsoft Research Asia(MSRA)提供的500个显着对象数据库图像进行了实验,取β〜2 = 0.3,F-measure的值高达0.816。结果表明,该方法可以有效地提取不同内容,不同目标位置和大小的图像显着区域,并且具有位置和大小上的适应性。

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