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    • 1. 发明授权
    • Methods and system for analyzing and rating images for personalization
    • 用于个性化分析和评估图像的方法和系统
    • US09042640B2
    • 2015-05-26
    • US13349751
    • 2012-01-13
    • Raja BalaZhigang FanHengzhou DingJan P. AllebachCharles A. BoumanReuven J. Sherwin
    • Raja BalaZhigang FanHengzhou DingJan P. AllebachCharles A. BoumanReuven J. Sherwin
    • G06K9/62G06K9/00G06K9/32
    • G06K9/00671G06K9/3258
    • As set forth herein, a computer-implemented method facilitates pre-analyzing an image and automatically suggesting to the user the most suitable regions within an image for text-based personalization. Image regions that are spatially smooth and regions with existing text (e.g. signage, banners, etc.) are primary candidates for personalization. This gives rise to two sets of corresponding algorithms: one for identifying smooth areas, and one for locating text regions. Smooth regions are found by dividing the image into blocks and applying an iterative combining strategy, and those regions satisfying certain spatial properties (e.g. size, position, shape of the boundary) are retained as promising candidates. In one embodiment, connected component analysis is performed on the image for locating text regions. Finally, based on the smooth and text regions found in the image, several alternative approaches are described herein to derive an overall metric for “suitability for personalization.”
    • 如本文所述,计算机实现的方法有助于预分析图像并且自动地向用户建议图像内的最合适的区域用于基于文本的个性化。 具有空间平滑的图像区域和具有现有文本的区域(例如标牌,横幅等)是用于个性化的主要候选者。 这产生了两组相应的算法:一种用于识别平滑区域,一种用于定位文本区域。 通过将图像划分成块并应用迭代组合策略来找到平滑区域,并且满足某些空间属性(例如,边界的大小,位置,形状)的那些区域被保留为有希望的候选者。 在一个实施例中,对用于定位文本区域的图像执行连接分量分析。 最后,基于图像中发现的平滑和文本区域,本文描述了几种替代方法,以得出“适合个性化”的总体度量。
    • 2. 发明申请
    • METHODS AND SYSTEM FOR ANALYZING AND RATING IMAGES FOR PERSONALIZATION
    • 用于分析和评估个性化图像的方法和系统
    • US20130182946A1
    • 2013-07-18
    • US13349751
    • 2012-01-13
    • Raja BalaZhigang FanHengzhou DingJan P. AllebachCharles A. BoumanReuven J. Sherwin
    • Raja BalaZhigang FanHengzhou DingJan P. AllebachCharles A. BoumanReuven J. Sherwin
    • G06K9/46G06K9/62
    • G06K9/00671G06K9/3258
    • As set forth herein, a computer-implemented method facilitates pre-analyzing an image and automatically suggesting to the user the most suitable regions within an image for text-based personalization. Image regions that are spatially smooth and regions with existing text (e.g. signage, banners, etc.) are primary candidates for personalization. This gives rise to two sets of corresponding algorithms: one for identifying smooth areas, and one for locating text regions. Smooth regions are found by dividing the image into blocks and applying an iterative combining strategy, and those regions satisfying certain spatial properties (e.g. size, position, shape of the boundary) are retained as promising candidates. In one embodiment, connected component analysis is performed on the image for locating text regions. Finally, based on the smooth and text regions found in the image, several alternative approaches are described herein to derive an overall metric for “suitability for personalization.”
    • 如本文所述,计算机实现的方法有助于预分析图像并且自动地向用户建议图像内的最合适的区域用于基于文本的个性化。 具有空间平滑的图像区域和具有现有文本的区域(例如标牌,横幅等)是用于个性化的主要候选者。 这产生了两组相应的算法:一种用于识别平滑区域,一种用于定位文本区域。 通过将图像划分成块并应用迭代组合策略来找到平滑区域,并且满足某些空间属性(例如,边界的大小,位置,形状)的那些区域被保留为有希望的候选者。 在一个实施例中,对用于定位文本区域的图像执行连接分量分析。 最后,基于图像中发现的平滑和文本区域,本文描述了几种替代方法,以得出“适合个性化”的总体度量。
    • 5. 发明授权
    • Finding text in natural scenes
    • 在自然场景中寻找文字
    • US08837830B2
    • 2014-09-16
    • US13494173
    • 2012-06-12
    • Raja BalaZhigang FanHengzhou DingJan P. AllebachCharles A. Bouman
    • Raja BalaZhigang FanHengzhou DingJan P. AllebachCharles A. Bouman
    • G06K9/34
    • G06K9/4604G06K9/3258G06K9/4638G06K2209/01G06T7/13G06T7/181G06T2207/10004
    • As set forth herein, systems and methods facilitate providing an efficient edge-detection and closed-contour based approach for finding text in natural scenes such as photographic images, digital, and/or electronic images, and the like. Edge information (e.g., edges of structures or objects in the images) is obtained via an edge detection technique. Edges from text characters form closed contours even in the presence of reasonable levels of noise. Closed contour linking and candidate text line formation are two additional features of the described approach. A candidate text line classifier is applied to further screen out false-positive text identifications. Candidate text regions for placement of text in the natural scene of the electronic image are highlighted and presented to a user.
    • 如本文所述,系统和方法有助于提供有效的边缘检测和基于闭合轮廓的方法,用于在诸如照相图像,数字和/或电子图像等的自然场景中查找文本。 通过边缘检测技术获得边缘信息(例如,图像中的结构或对象的边缘)。 即使存在合理的噪声水平,文本字符的边缘也会形成封闭的轮廓。 闭合轮廓链接和候选文本线形成是所述方法的两个附加特征。 应用候选文本行分类器进一步筛选出假阳性文本标识。 用于在电子图像的自然场景中放置文本的候选文本区域被突出显示并呈现给用户。