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Character segmentation and thresholding in low-contrast scene images

机译:低对比度场景图像中的字符分割和阈值化

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Abstract: We are developing a portable text-to-speech system for the vision impaired. The input image is acquired with a lightweight CCD camera that may be poorly focused and aimed, and perhaps taken under inadequate and uneven illumination. We therefore require efficient and effective thresholding and segmentation methods which are robust with respect to character contrast, font, size, and format. In this paper, we present a fast thresholding scheme which combines a local variance measure with a logical stroke-width method. An efficient post- thresholding segmentation scheme utilizing Fisher's linear discriminant to distinguish noise and character components functions as an effective pre-processing step for the application of commercial segmentation and character recognition methods. The performance of this fast new method compared favorably with other methods for the extraction of characters from uncontrolled illumination, omnifont scene images. We demonstrate the suitability of this method for use in an automated portable reader through a software implementation running on a laptop 486 computer in our prototype device. !6
机译:摘要:我们正在为视力障碍开发便携式文本到语音系统。用轻量级CCD相机获取输入图像,该摄像机可能略微聚焦和瞄准,并且可能在不充分和不均匀的照明下采取。因此,我们需要有效且有效的阈值和分割方法,这些方法对于字符对比度,字体,大小和格式而是鲁棒的。在本文中,我们介绍了一种快速阈值平面方案,它将局部方差测量与逻辑行程宽度法相结合。利用Fisher的线性判别来区分噪声和字符组件的有效后阈值分割方案用作应用商业分割和字符识别方法的有效预处理步骤。这种快速新方法的性能有利地与其他方法从不受控制的照明,Omnifont场景图像中提取了其他方法。我们通过在我们的原型设备中的笔记本电脑486计算机上运行的软件实现,展示了这种方法在自动便携式阅读器中使用的适用性。 !6

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