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公开(公告)号：US20050123198A1
公开(公告)日：2005-06-09
申请号：US10961403
申请日：2004-10-12
CPC分类号： G06K9/325 , G06K2209/01 , H04N1/40062
摘要： Pixels are classified as text; or “non-text” by responding to accumulated luminous brightness gradients within a predetermined pixel interior. Text and non-text image characteristics rest on estimating text-containing rectangles by determining a narrow width and a height of a peak in an interval of accumulated gradients around each pixel. The text characteristics also are inferred by detecting character corners by quantifying and smoothing gradient angles and by associating directional corner responses with each pixel.
摘要翻译： 像素被分类为文字; 或“非文本”，通过响应在预定像素内部的累积的发光亮度梯度。 文本和非文本图像特征依赖于通过确定围绕每个像素的累积梯度的间隔中的峰值的窄宽度和高度来估计包含文本的矩形。 通过量化和平滑梯度角以及通过将方向角响应与每个像素相关联来检测文字角，推断文本特征。
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公开(公告)号：US07616814B2
公开(公告)日：2009-11-10
申请号：US10961403
申请日：2004-10-12
CPC分类号： G06K9/325 , G06K2209/01 , H04N1/40062
摘要： Pixels are classified as text; or “non-text” by responding to accumulated luminous brightness gradients within a predetermined pixel interior. Text and non-text image characteristics rest on estimating text-containing rectangles by determining a narrow width and a height of a peak in an interval of accumulated gradients around each pixel. The text characteristics also are inferred by detecting character corners by quantifying and smoothing gradient angles and by associating directional corner responses with each pixel.
摘要翻译： 像素被分类为文字; 或“非文本”，通过响应在预定像素内部的累积的发光亮度梯度。 文本和非文本图像特征依赖于通过确定围绕每个像素的累积梯度的间隔中的峰值的窄宽度和高度来估计包含文本的矩形。 通过量化和平滑梯度角以及通过将方向角响应与每个像素相关联来检测文字角，推断文本特征。
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公开(公告)号：US08950456B2
公开(公告)日：2015-02-10
申请号：US13508855
申请日：2010-10-25
申请人： Christophe Laurent , David Dean , David Lavialle
发明人： Christophe Laurent , David Dean , David Lavialle
CPC分类号： B60C15/06 , B60B21/104 , B60C1/00 , B60C15/00 , B60C15/0009 , B60C15/02 , B60C15/0607 , B60C2001/0058 , B60C2015/009 , B60C2015/0614 , B60C2015/0617 , B60C2015/0621 , Y10T152/10819 , Y10T152/10828 , Y10T152/10837 , Y10T152/10846
摘要： An assembly including a tire having beads, said bead axially including outside the turn-up a layer of a material defining a bead outer profile, such that the distance A, between the carcass frame and the bead outer profile, is as defined in formula (Z), B being the distance between the end of the turn-up, said bead including first and second profiles between the carcass frame and the turn-up, the first profile extends from the bead wire and is made of a material having an extension secant modulus at a 10% elongation higher than 20 MPa, a second profile arranged in the bead such as to be in contact with a surface of the first profile and the turn-up, made of a material having an extension secant modulus at a 10% elongation of at least 7 MPa and an extension secant modulus at a 100*% extension of at least 4.5 MPa.
摘要翻译： 一种包括具有珠的轮胎的组件，所述胎圈在轴向上包括限定出胎圈外轮廓的材料的一层，使得胎体框架和胎圈外轮廓之间的距离A如公式（ Z），B是折叠端部之间的距离，所述胎圈包括胎体框架和翻转之间的第一和第二轮廓，第一轮廓从胎圈丝延伸并且由具有延伸部的材料制成 在10％伸长率下高于20MPa的正割模量，布置在胎圈中的第二轮廓，以便与第一轮廓的表面接触，并且由具有10秒的延伸分割模数的材料制成 至少7MPa的伸长率和至少4.5MPa的100 *％延伸率的延伸法线模量。
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公开(公告)号：US20130318418A1
公开(公告)日：2013-11-28
申请号：US13477610
申请日：2012-05-22
申请人： Ferdinando Bedeschi , Roberto Gastaldi , Christophe Laurent , Paolo Amato , Sandro Bellini , Alessandro Tomasoni
发明人： Ferdinando Bedeschi , Roberto Gastaldi , Christophe Laurent , Paolo Amato , Sandro Bellini , Alessandro Tomasoni
CPC分类号： G06F11/1048 , G11C13/0004 , G11C29/028 , G11C2029/0411 , H03M13/1515 , H03M13/152 , H03M13/19 , H03M13/353 , H03M13/3715
摘要： Subject matter disclosed herein relates to memory operations regarding error correction or error detection.
摘要翻译： 本文公开的主题涉及关于纠错或错误检测的存储器操作。
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公开(公告)号：US20050004848A1
公开(公告)日：2005-01-06
申请号：US10883598
申请日：2004-07-01
CPC分类号： G06Q30/08
摘要： The present invention relates to a method of real-time on-line auction processing implemented by a bid server, comprising the following steps: reception of bid orders relating to at least one good or service put up for sale by auction, each bid order being associated with an amount; selection of a bid order, from among the bid orders received whose amount is equal to the highest amount of all the bid orders received. Furthermore, in this method a timeout is triggered whenever the server receives a bid order of an amount strictly greater than the highest amount of all the bid orders received previously and relating to the said good or service; and during the selection step, a bid order is selected randomly from among those received during the timeout period. The invention applies also to two other types of auction methods in which the price of the good or service put up for sale is fixed by the server.
摘要翻译： 本发明涉及一种由投标服务器实施的实时在线拍卖处理方法，包括以下步骤：通过拍卖接收与至少一件商品或服务有关的投标书，每个投标订单为 与数量相关联; 从接收到的所有投标订单的最高金额等于收到的投标订单中选择一个投标单。 此外，在该方法中，每当服务器收到严格大于先前接收到的与所述商品或服务相关的所有投标订单的最高金额的金额的投标订单时，触发超时; 并且在选择步骤期间，从超时期间接收的接收中随机选择出价顺序。 本发明也适用于服务器固定出售的商品或服务的价格的两种其他类型的拍卖方式。
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6.发明授权公开(公告)号：US07856123B2
公开(公告)日：2010-12-21
申请号：US11628321
申请日：2004-06-04
IPC分类号： G06K9/00
CPC分类号： G06K9/6235 , G06K9/00275
摘要： The invention relates to a method for recognizing faces in digital images consisting in providing for a knowledge base which contains face images and is hierarchical into several classes each of which comprises different images of the same person. The invention relates to pre-processing said knowledge base in such a way that a minimization of variance in each class and a maximization of variance between different classes are simultaneously obtainable, thereby making it possible to form a vectorial base comprising the discriminant component of said knowledge base. The comparison of a recognizable face with a pre-processed reference face such as the knowledge base and an eventual reconstruction of a recognized face are also disclosed.
摘要翻译： 本发明涉及一种用于识别数字图像中的面部的方法，包括提供包含面部图像的知识库，并且被分层成几个类别，每个类别包括同一人的不同图像。 本发明涉及以这样的方式预处理所述知识库，使得可以同时获得每个类中的方差最小化和不同类之间的最大化方差，由此可以形成包括所述知识的判别分量的矢量基 基础。 还公开了可识别面部与预处理参考面（例如知识库）和识别面部的最终重建的比较。
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公开(公告)号：US20100169741A1
公开(公告)日：2010-07-01
申请号：US12623310
申请日：2009-11-20
申请人： Christophe Laurent , Paolo Amato , Marco Sforzin , Corrado Villa
发明人： Christophe Laurent , Paolo Amato , Marco Sforzin , Corrado Villa
CPC分类号： G06F11/1068 , G11C29/52 , H03M13/2909
摘要： A memory array and a method of writing to a unidirectional non-volatile storage cell are disclosed whereby a user data word is transformed to an internal data word and written to one or more unidirectional data storage cells according to a cell coding scheme. A check word may be generated that corresponds to the internal data word. In some embodiments, the check word may be generated by inverting one or more bits of an intermediate check word. Other embodiments may be described and claimed.
摘要翻译： 公开了一种写入单向非易失性存储单元的存储器阵列和方法，其中用户数据字被转换为内部数据字，并根据小区编码方案写入一个或多个单向数据存储单元。 可以生成对应于内部数据字的检查字。 在一些实施例中，可以通过反转中间检查字的一个或多个位来产生检验字。 可以描述和要求保护其他实施例。
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8.发明申请公开(公告)号：US20080317352A1
公开(公告)日：2008-12-25
申请号：US11597482
申请日：2004-05-24
申请人： Julien Ros , Christophe Laurent
发明人： Julien Ros , Christophe Laurent
IPC分类号： G06K9/46
CPC分类号： G06F17/30247 , G06K9/522 , G06K9/6857
摘要： A method of characterizing a digital image, in which a point of interest (PI) in the detected in the image. For each θ of a plurality I of different prescribed orientations in the digital image a family {fθ(k)(n)}1≦k≦K of K one-dimensional lines fθ(k)(n) of points is extracted from a region (RPI) of the image along K straight lines of orientation (θ), and for each line fθ(k)(n) and for each sub-sampling level s, a foveal energy signal Eθ,s(k)(n) is calculated using foveal wavelets. The signals Eθ,s(k)(n)) on the K lines and their arguments n are used to calculate a foveal signature SI characterizing the working region.
摘要翻译： 一种表征图像中检测到的感兴趣点（PI）的数字图像的方法。 对于数字图像中的不同规定取向的多个I的每个θ，提取K个一维线f（t）（k）（n）的族（f）（k）（n）} 1 <= k <= K 沿着K直线取向（theta）的图像的区域（RPI），并且对于每个线fta（k）（n），并且对于每个子采样水平s，中心凹能量信号Etheta，s（k）（ n）使用中心凹小波计算。 K线上的信号Etheta，s（k）（n））及其参数n用于计算表征工作区域的中心凹签名SI。
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公开(公告)号：US07206769B2
公开(公告)日：2007-04-17
申请号：US09798739
申请日：2001-03-02
IPC分类号： G06Q99/00
CPC分类号： G07F7/0866 , G06Q20/06 , G06Q20/10 , G06Q20/363 , G06Q20/367 , G06Q20/3672 , G06Q20/4012
摘要： The electronic wallet system comprises a plurality of devices interconnected through a local network and capable of conducting electronic business transaction on an open network (40). Each device contains a smart card reader. A plurality of smart cards (31–3p) represent the electronic purses of the system. One of the devices comprises an entity called the server which contains a list of purses liable to receive tokens from others purses of the system. The tokens transferred between purses are stored temporally by said server.Application to a family wallet system allowing children to participate to electronic commerce.The system makes it possible to transfer tokens from one first purse to a second purse without having in hands the smart card corresponding to the second purse.
摘要翻译： 电子钱包系统包括通过本地网络互连并能够在开放网络（40）上进行电子商务交易的多个设备。 每个设备都包含智能卡读卡器。 多个智能卡（31-3p）表示系统的电子钱包。 其中一个设备包括称为服务器的实体，该实体包含易于从系统的其他钱包接收令牌的钱包列表。 在钱包之间传送的令牌由所述服务器临时存储。
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10.发明申请Method and device for detection of points of interest in a source digital image, corresponding computer program and data support 审中-公开用于检测源数字图像中的兴趣点的方法和设备，相应的计算机程序和数据支持公开(公告)号：US20060257028A1
公开(公告)日：2006-11-16
申请号：US10541118
申请日：2003-03-14
IPC分类号： G06K9/46
CPC分类号： G06K9/4671 , G06F16/583 , G06K9/527 , G06T7/12 , G06T7/168 , G06T2207/20064 , G06T2207/20164
摘要： The invention related to a method for detection of points of interest in a source digital image, by means of a wavelet transformation associating a sub-sampled image, called a scaled image, with a source image and wavelet coefficients corresponding to at least one detail image, for at least one level of decomposition, a point of interest being a point associated with a region of the image with high frequencies. The method comprises the following steps:—application of said wavelet transformation to said source image, generation of a single tree structure from the wavelet coefficients of each of said detail images and selection of at least one point of interest by analysis of said tree structure.
摘要翻译： 本发明涉及一种用于检测源数字图像中的兴趣点的方法，借助于将称为缩放图像的子采样图像与源图像相关联的小波变换和与至少一个细节图像相对应的小波系数 对于至少一级的分解，兴趣点是与具有高频率的图像的区域相关联的点。 该方法包括以下步骤：将所述小波变换应用于所述源图像，从每个所述细节图像的小波系数生成单个树结构，以及通过分析所述树结构来选择至少一个兴趣点。
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