Scene Text Aware Image Retargeting

D. Patel, S. Raman
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Abstract

Extensive use of text labels and symbols available in the digital media for interpretation and communication of information has gained a lot of attention in the era of digital media. Access of the images with scene text in it through different display devices tend to deform the scene text region while resizing for better viewing experience. We propose an image retargeting operator, which is aware of the scene text present in the image. We perform the normal seam carving depending on the content of the image for the non-text region. We find the target size of each scene text region during the seam carving process. Having the location and the size of the scene text region in the retargeted image, we perform content-aware warping for every scene text region in the image. We evaluate the performance of the proposed scene text aware image retargeting operator using image retargeting quality assessment metric for visual retargeting quality and text recognition efficiency for text readability. We show the quality of the proposed approach through results and discussion.
场景文本感知图像重定位
在数字媒体时代,广泛使用数字媒体中的文本标签和符号来解释和传播信息已经引起了人们的广泛关注。通过不同的显示设备访问包含场景文本的图像,在调整大小以获得更好的观看体验时,往往会使场景文本区域变形。我们提出了一种图像重定位算子,它可以识别图像中存在的场景文本。对于非文本区域,我们根据图像的内容执行正常的接缝雕刻。我们在拼接过程中找到每个场景文本区域的目标尺寸。有了重定向图像中场景文本区域的位置和大小,我们对图像中的每个场景文本区域执行内容感知扭曲。我们使用图像重定向质量评估指标评估视觉重定向质量和文本识别效率评估文本可读性来评估所提出的场景文本感知图像重定向算子的性能。我们通过结果和讨论来展示所提出方法的质量。
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