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    • 55. 发明授权
    • Method of detecting and correcting digital images of books in the book spine area
    • 检索和纠正书脊图书籍数字图像的方法
    • US08457403B2
    • 2013-06-04
    • US13111199
    • 2011-05-19
    • Jia LiMikhail BrusnitsynSujay Sukumaran
    • Jia LiMikhail BrusnitsynSujay Sukumaran
    • G06K9/34
    • H04N1/3873G06K2009/363H04N1/387
    • An image of a scanned book is segmented using a feature image to map pixels corresponding to a page area and to create page objects and detect borders of the page. A book spine region is detected by locating a plain background area between two of the page objects, analyzing the page borders to detect their shape, and analyzing their shape to detect the book spine end points. Using the page borders, the feature image is examined to detect top-to-bottom and bottom-to-top declines in pixel values to determine the corners of a shadow distortion in the original scanned image. Squeeze and curvature distortion are also detected. A Bezier curve is used to model each of the three distortions detected on the page. The detected distortion is corrected by first defining a trapezoidal correction area. The intensity, squeeze, and curvature corrections are then applied along lines within the trapezoidal correction area.
    • 使用特征图像对扫描书的图像进行分割,以对应于页面区域的像素映射并创建页面对象并检测页面的边界。 通过在两个页面对象之间定位一个简单的背景区域,分析页面边框以检测其形状并分析其形状以检测书脊柱端点来检测书脊区域。 使用页面边框,检查特征图像以检测像素值中的从上到下和从底部到顶部的下降,以确定原始扫描图像中阴影失真的角。 也检测到挤压和曲率失真。 贝塞尔曲线用于对页面上检测到的三个失真进行建模。 通过首先定义梯形校正区域来校正检测到的失真。 然后沿着梯形校正区域内的线施加强度,挤压和曲率校正。
    • 57. 发明申请
    • STUDYING AESTHETICS IN PHOTOGRAPHIC IMAGES USING A COMPUTATIONAL APPROACH
    • 使用计算方法研究摄影图像中的美学
    • US20130011070A1
    • 2013-01-10
    • US13542326
    • 2012-07-05
    • Ritendra DattaJia LiJames Z. Wang
    • Ritendra DattaJia LiJames Z. Wang
    • G06K9/62G06K9/46
    • G06K9/6228G06K9/00624G06K9/4652G06K9/4671
    • The aesthetic quality of a picture is automatically inferred using visual content as a machine learning problem using, for example, a peer-rated, on-line photo sharing Website as data source. Certain visual features of images are extracted based on the intuition that they can discriminate between aesthetically pleasing and displeasing images. A one-dimensional support vector machine is used to identify features that have noticeable correlation with the community-based aesthetics ratings. Automated classifiers are constructed using the support vector machines and classification trees, with a simple feature selection heuristic being applied to eliminate irrelevant features. Linear regression on polynomial terms of the features is also applied to infer numerical aesthetics ratings.
    • 使用例如同行评级的在线照片共享网站作为数据源,使用视觉内容作为机器学习问题自动推断图片的美学品质。 基于它们可以在美学上令人不愉快的图像之间区分的直觉来提取图像的某些视觉特征。 一维支持向量机用于识别与基于社区的美学评级具有显着相关性的特征。 使用支持向量机和分类树构建自动分类器,并采用简单的特征选择启发式来消除不相关的特征。 特征的多项式项的线性回归也用于推断数字美学评级。
    • 60. 发明申请
    • ON-SITE COMPOSITION AND AESTHETICS FEEDBACK THROUGH EXEMPLARS FOR PHOTOGRAPHERS
    • 现场组合和美学反馈通过摄影师的例证
    • US20120268612A1
    • 2012-10-25
    • US13493564
    • 2012-06-11
    • James Z. WangJia LiLei YaoPoonam SuryanarayanMu Qiao
    • James Z. WangJia LiLei YaoPoonam SuryanarayanMu Qiao
    • H04N5/225
    • G06K9/6267G06K9/00624G06K9/46G06K9/4652G06K9/4671G06K9/6228H04N5/23222
    • A comprehensive system to enhance the aesthetic quality of the photographs captured by mobile consumers provides on-site composition and aesthetics feedback through retrieved examples. Composition feedback is qualitative in nature and responds by retrieving highly aesthetic exemplar images from the corpus which are similar in content and composition to the snapshot. Color combination feedback provides confidence on the snapshot to contain good color combinations. Overall aesthetics feedback predicts the aesthetic ratings for both color and monochromatic images. An algorithm is used to provide ratings for color images, while new features and a new model are developed to treat monochromatic images. This system was designed keeping the next generation photography needs in mind and is the first of its kind. The feedback rendered is guiding and intuitive in nature. It is computed in situ while requiring minimal input from the user.
    • 提高移动消费者拍摄的照片的美学质量的全面系统通过检索的例子提供现场构图和美学反馈。 组合反馈本质上是定性的,并通过从语料库中检索与内容和构图相似的快照的高度审美的示例图像来进行响应。 颜色组合反馈提供了对快照的信心,以包含良好的颜色组合。 整体美学反馈预测了彩色和单色图像的审美等级。 一种算法用于提供彩色图像的等级,同时开发新特征和新模型来处理单色图像。 该系统的设计保持了下一代摄影的需要,是同类产品中的第一个。 呈现的反馈本质上是指导和直观的。 它是原地计算的,同时需要用户的最小输入。