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    • 2. 发明授权
    • Method and apparatus for windowing and image rendition
    • 用于窗口和图像再现的方法和装置
    • US07218332B2
    • 2007-05-15
    • US10135139
    • 2002-04-30
    • Hui ChengYing-wei Lin
    • Hui ChengYing-wei Lin
    • G06T15/00
    • H04N1/00G06T11/00H04N1/00798
    • Systems and methods are presented for processing and rendering image data during a single pass through the image data. A method includes loading scanlines of image data into a rolling band buffer, performing a windowing technique on the image data, and determining if a class change was experienced by any window having a portion in an output scanline of the buffer. The method further includes processing image data in the output scanline for a window portion that experienced a class change, using a blended rendering algorithm. If no class change is detected, the method includes processing image data in the output scanline for the window portion using a class-based rendering algorithm. The method optionally includes rendering processed image data for the output scanline to a rendering device. According to other features, an apparatus includes a rolling band buffer, a windowing processor, class-based rendering algorithms, and a blended rendering algorithm.
    • 呈现系统和方法,用于在单次传递图像数据期间处理和渲染图像数据。 一种方法包括将图像数据的扫描线加载到滚动带缓冲器中,对图像数据执行加窗技术,以及确定是否由具有缓冲器的输出扫描线中的一部分的任何窗口经历了类别改变。 该方法还包括使用混合渲染算法来处理经历类别改变的窗口部分的输出扫描线中的图像数据。 如果没有检测到类更改,则该方法包括使用基于类的呈现算法来处理窗口部分的输出扫描线中的图像数据。 该方法可选地包括将处理的输出扫描线的图像数据渲染到呈现设备。 根据其他特征,一种装置包括滚动带缓冲器,加窗处理器,基于类的渲染算法和混合渲染算法。
    • 4. 发明授权
    • Picture/graphics classification system and method
    • 图片/图形分类系统和方法
    • US06983068B2
    • 2006-01-03
    • US09965922
    • 2001-09-28
    • Salil PrabhakarHui ChengZhigang FanJohn C. HandleyYing-wei Lin
    • Salil PrabhakarHui ChengZhigang FanJohn C. HandleyYing-wei Lin
    • G06K9/00
    • G06K9/00456
    • A method and system for image processing, in conjunction with classification of images between natural pictures and synthetic graphics, using SGLD texture (e.g., variance, bias, skewness, and fitness), color discreteness (e.g., R—L, R—U, and R—V normalized histograms), or edge features (e.g., pixels per detected edge, horizontal edges, and vertical edges) is provided. In another embodiment, a picture/graphics classifier using combinations of SGLD texture, color discreteness, and edge features is provided. In still another embodiment, a “soft” image classifier using combinations of two (2) or more SGLD texture, color discreteness, and edge features is provided. The “soft” classifier uses image features to classify areas of an input image in picture, graphics, or fuzzy classes.
    • 一种用于图像处理的方法和系统,结合使用SGLD纹理(例如,方差,偏差,偏度和适应度)的自然图像和合成图像之间的图像分类,颜色离散性(例如,R SUB 提供了一个或多个边缘特征(例如每个检测到的边缘,水平边缘和垂直边缘的像素)。 在另一个实施例中,提供了使用SGLD纹理,颜色离散性和边缘特征的组合的图片/图形分类器。 在另一个实施例中,提供了使用两(2)或更多SGLD纹理,颜色离散性和边缘特征的组合的“软”图像分类器。 “软”分类器使用图像特征来对图像,图形或模糊类中的输入图像的区域进行分类。
    • 8. 发明授权
    • Device of handling roller for passbook
    • 存折处理辊的装置
    • US07387199B2
    • 2008-06-17
    • US11528311
    • 2006-09-28
    • Hui ChengKazushi YoshidaTatsuma Suzuki
    • Hui ChengKazushi YoshidaTatsuma Suzuki
    • B65G13/06
    • B65H27/00B65H2403/735B65H2404/1122
    • A passbook conveyance roller device comprises a conveyance roller and a pinch roller, which are arranged to be opposed to each other, to convey a passbook. The conveyance roller comprises an inner ring member connected to a drive shaft, a metallic outer ring member, and a rubber member fixed to, for example, an outer peripheral surface of the inner ring member and press fitted into an inner peripheral surface of the outer ring member to give elastic forces to the inner peripheral surface of the outer ring member in a plurality of positions, which are spaced circumferentially at predetermined intervals from one another and arranged in point symmetry. Both the inner ring member and the outer ring member are rotated through the elastic member when a load torque on the outer ring member is less than a set torque set by the elastic forces of the rubber member. Relative slip is generated between the inner peripheral surface of the outer ring member and the rubber member when a load torque on the outer ring member is equal to or larger than the set torque.
    • 存折传送辊装置包括彼此相对布置的传送辊和夹送辊,以传送存折。 传送辊包括连接到驱动轴的内圈构件,金属外圈构件和固定到例如内圈构件的外周面的橡胶构件,并且压配合到外圈的内周面中 在多个位置上以规定的间隔彼此间隔设置并以点对称的方式间隔地向外圈构件的内周面施加弹性力。 当外圈构件上的负载扭矩小于由橡胶构件的弹力设定的设定扭矩时,内圈构件和外圈构件都通过弹性构件旋转。 当外圈构件的负载扭矩等于或大于设定扭矩时,在外圈构件的内周面与橡胶构件之间产生相对滑移。
    • 10. 发明授权
    • Exemplar-based heterogeneous compositional method for object classification
    • 用于对象分类的基于示例的异构组合方法
    • US08233704B2
    • 2012-07-31
    • US12136138
    • 2008-06-10
    • Feng HanHui ChengJiangjian XiaoHarpreet Singh Sawhney
    • Feng HanHui ChengJiangjian XiaoHarpreet Singh Sawhney
    • G06K9/62G06E1/00G06E3/00G06F15/18G06G7/00
    • G06K9/3241G06K9/6256G06K9/6292
    • A method for automatically generating a strong classifier for determining whether at least one object is detected in at least one image is disclosed, comprising the steps of: (a) receiving a data set of training images having positive images; (b) randomly selecting a subset of positive images from the training images to create a set of candidate exemplars, wherein said positive images include at least one object of the same type as the object to be detected; (c) training a weak classifier based on at least one of the candidate exemplars, said training being based on at least one comparison of a plurality of heterogeneous compositional features located in the at least one image and corresponding heterogeneous compositional features in the one of set of candidate exemplars; (d) repeating steps (c) for each of the remaining candidate exemplars; and (e) combining the individual classifiers into a strong classifier, wherein the strong classifier is configured to determine the presence or absence in an image of the object to be detected.
    • 公开了一种用于自动生成强分类器以确定在至少一个图像中是否检测到至少一个对象的方法,包括以下步骤:(a)接收具有正图像的训练图像的数据集; (b)从所述训练图像中随机选择正图像的子集以创建一组候选样本,其中所述正图像包括与所述待检测对象相同类型的至少一个对象; (c)基于所述候选样本中的至少一个来训练弱分类器,所述训练基于位于所述至少一个图像中的多个异质成分特征和所述一个图像中的一个中的对应的异质组成特征的至少一个比较 候选人样本 (d)为每个其余的候选样本重复步骤(c); 以及(e)将各个分类器组合成强分类器,其中强分类器被配置为确定待检测对象的图像中的存在或不存在。