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1.发明授权System and method for determining ridge counts in fingerprint image processing 失效用于确定指纹图像处理中的脊数的系统和方法
公开(公告)号：US6111978A
公开(公告)日：2000-08-29
申请号：US837069
申请日：1997-04-11
IPC分类号： G06K9/00
CPC分类号： G06K9/00067
摘要： A computer based image processing system uses an extraction process to include a pressure invariant feature for measuring distances between minutiae. The feature extraction process identifies one or more of the following features of the fingerprint: an orthogonal image contrast, a parallel image contrast, and a feature confidence. A ridge counter process, executing on the computer system, determines the number of ridges (ridge count) running across two given points and further qualifies (invalidates) this count if the confidence value of the pixels in the region adjoining the region is not reliable. The ridge count feature between minutiae is used for determining reliable features when matching fingerprints.
摘要翻译： 基于计算机的图像处理系统使用提取过程来包括用于测量细节之间的距离的压力不变特征。 特征提取过程识别指纹的以下特征中的一个或多个：正交图像对比度，平行图像对比度和特征置信度。 在计算机系统上执行的脊计数器处理确定在两个给定点上运行的脊数（脊数），并且如果与该区域相邻的区域中的像素的置信度值不可靠，则进一步限定（无效）该计数。 细节之间的脊数特征用于在匹配指纹时确定可靠特征。
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2.发明授权
公开(公告)号：US6072895A
公开(公告)日：2000-06-06
申请号：US823637
申请日：1997-03-25
IPC分类号： G06K9/00
CPC分类号： G06K9/00067
摘要： A computer based image processing system uses an extraction process to extract one or more features from a target fingerprint image. The feature extraction process identifies one or more of the following features of the fingerprint: orthogonal image contrast, parallel image contrast, feature confidence, distance between two minutia, neighbor information, angle-distance between two minutia, angle-distance neighbor information, minutiae density, ridge length, ridge density, and wiggle factor. A pruner process, executing on the computer system, determines if one or more of the features meet any one or more of a set of pruning criteria, and that deletes the minutiae if the pruning criteria is met. The pruning process is based on (i) locations and image contrast, (ii) the distances, orientations of minutiae and (iii) spatial distributions of minutiae and ridges of the fingerprint. The minutiae that remain after the pruning can be used for feature matching.
摘要翻译： 基于计算机的图像处理系统使用提取过程从目标指纹图像中提取一个或多个特征。 特征提取过程识别指纹的以下特征中的一个或多个：正交图像对比度，平行图像对比度，特征置信度，两个细节之间的距离，相邻信息，两个细节之间的角度距离，角距邻近信息，细节密度 ，脊长，脊密度和摆动因子。 在计算机系统上执行的修剪过程确定一个或多个特征是否满足一组修剪标准中的一个或多个，并且如果满足修剪标准则删除细节。 修剪过程基于（i）位置和图像对比度，（ii）细节的距离，方向和（iii）指纹的细节和脊的空间分布。 修剪后留下的细节可用于特征匹配。
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3.发明授权System and method for determining ridge counts in fingerprint image processing 失效用于确定指纹图像处理中的脊数的系统和方法公开(公告)号：US06266433B1
公开(公告)日：2001-07-24
申请号：US09302109
申请日：1999-04-29
IPC分类号： G06K900
CPC分类号： G06K9/00067
摘要： A computer based image processing system uses an extraction process to include a pressure invariant feature for measuring distances between minutiae. The feature extraction process identifies one or more of the following features of the fingerprint: an orthogonal image contrast, a parallel image contrast, and a feature confidence. A ridge counter process, executing on the computer system, determines the number of ridges (ridge count) running across two given points and further qualifies (invalidates) this count if the confidence value of the pixels in the region adjoining the region is not reliable. The ridge count feature between minutiae is used for determining reliable features when matching fingerprints.
摘要翻译： 基于计算机的图像处理系统使用提取过程来包括用于测量细节之间的距离的压力不变特征。 特征提取过程识别指纹的以下特征中的一个或多个：正交图像对比度，平行图像对比度和特征置信度。 在计算机系统上执行的脊计数器处理确定在两个给定点上运行的脊数（脊数），并且如果与该区域相邻的区域中的像素的置信度值不可靠，则进一步限定（无效）该计数。 细节之间的脊数特征用于在匹配指纹时确定可靠特征。
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公开(公告)号：US09396621B2
公开(公告)日：2016-07-19
申请号：US13428982
申请日：2012-03-23
CPC分类号： G06K9/00771 , G06K7/10009 , G06K9/00335 , G06K9/6256 , G06K9/6269 , G07G1/0036 , G07G1/0045 , G07G1/009 , H04N7/18 , H04N7/183
摘要： Embodiments of the present invention provide a system, method, and program product to determine whether a product has been successfully purchased by identifying in a video record when a movement of a product adjacent to a scanner occurs, and whether the scanner did not record a purchase transaction at that time; measuring a difference in time between the time of the movement of the product and a time of another movement of a product, and determining by a trained support vector machine a likelihood that the product was successfully purchased. Alternately, the difference in time can be measured between the time of the movement of the product and a time of a transaction record, or between the time of the movement of the product and a boundary time. The support vector machine can use a radial basis function kernel and can generate a decision value and a confidence score.
摘要翻译： 本发明的实施例提供一种系统，方法和程序产品，用于通过在与扫描仪相邻的产品的移动发生时识别产品在视频记录中是否成功购买，以及扫描仪是否没有记录购买 当时交易; 测量产品移动时间与产品的另一次移动时间之间的时间差，以及由经过训练的支持向量机确定产品被成功购买的可能性。 或者，可以在产品移动时间与交易记录时间之间，或在产品移动时间与边界时间之间测量时间差。 支持向量机可以使用径向基函数内核，并可以生成决策值和置信度分数。
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公开(公告)号：US09330315B2
公开(公告)日：2016-05-03
申请号：US13591530
申请日：2012-08-22
CPC分类号： G06K9/00771 , G06T7/11 , G06T7/143 , G06T7/194 , G06T2207/30232
摘要： A computer identifies a proto-object in a digital image using a background subtraction method, the proto-object being associated with a lighting artifact in the surveillance region. The background subtraction method preserves boundary details and interior texture details of proto-objects associated with lighting artifacts. A plurality of characteristics of the proto-object digital data are determined, the characteristics, individually or in combination, distinguish a proto-object related to a lighting artifact from its background. A learning machine, trained with the plurality of characteristics of proto-objects classified as either foreground or not foreground, determines a likelihood that the plurality of characteristics is associated with a foreground object.
摘要翻译： 计算机使用背景减法方法识别数字图像中的原型对象，原型对象与监视区域中的照明伪像相关联。 背景减法方法保留与照明伪像相关联的原始对象的边界细节和内部纹理细节。 确定原始对象数字数据的多个特征，特征单独或组合地将与照明伪影相关的原始物体与其背景区分开。 用分类为前景或非前景的原型对象的多个特征训练的学习机器确定多个特征与前景对象相关联的可能性。
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公开(公告)号：US09158976B2
公开(公告)日：2015-10-13
申请号：US13110331
申请日：2011-05-18
IPC分类号： G08B13/196 , G06K9/00 , G06F19/24 , G06K9/62
CPC分类号： G06K9/00771 , G06F19/24 , G06K9/6284 , G06T7/251 , G08B13/19606
摘要： Local models learned from anomaly detection are used to rank detected anomalies. The local models include image feature values extracted from an image field of video image data with respect to different predefined spatial and temporal local units, wherein anomaly results are determined by failures to fit to applied anomaly detection module local models. Image features values extracted from the image field local units associated with anomaly results are normalized, and image feature values extracted from the image field local units are clustered. Weights for anomaly results are learned as a function of the relations of the normalized extracted image feature values to the clustered image feature values. The normalized values are multiplied by the learned weights to generate ranking values to rank the anomalies.
摘要翻译： 从异常检测中获取的局部模型用于对检测到的异常进行排序。 本地模型包括从视频图像数据的图像字段提取的关于不同的预定空间和时间局部单位的图像特征值，其中异常结果由适合于应用的异常检测模块本地模型的失败确定。 从与异常结果相关联的图像场本地单元提取的图像特征值被归一化，并且从图像场本地单元提取的图像特征值被聚类。 根据归一化提取的图像特征值与聚类图像特征值的关系来学习异常结果的权重。 归一化值乘以学习权重以产生排序值以排除异常。
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公开(公告)号：US09050984B2
公开(公告)日：2015-06-09
申请号：US13451610
申请日：2012-04-20
CPC分类号： B61L23/042 , G06T7/0004 , G06T7/194 , G06T2207/30136 , G06T2207/30164 , G06T2207/30242 , G06T2207/30252
摘要： A method and system for inspecting railway components. The method includes receiving a stream of images containing railway components, detecting a railway component in each image, generating a plurality of feature vectors for each railway component image, measuring the dissimilarity between the railway component and a set of railway components detected in preceding images, in a sliding window, based on the feature vectors.
摘要翻译： 检查铁路部件的方法和系统。 该方法包括接收包含铁路部件的图像流，检测每个图像中的铁路部件，为每个铁路部件图像生成多个特征向量，测量铁路部件与在先前图像中检测到的一组铁路部件之间的不相似性， 在滑动窗口中，基于特征向量。
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公开(公告)号：US08751414B2
公开(公告)日：2014-06-10
申请号：US13100868
申请日：2011-05-04
CPC分类号： G06F11/0751 , G06F11/3058 , G06F11/3082
摘要： A method, data processing system, and computer program product for identifying abnormalities in data. A model representing a plurality of modes for an activity generated from training data is retrieved. The training data includes a first plurality of measurements of a first performance of the activity over a period of time. Each of the plurality of modes is identified as one of normal and abnormal. Activity data including a second plurality of measurements of a second performance of the activity is received. A portion of the activity data is compared with the plurality of modes in the model. A notification of an abnormality in the second performance of the activity is generated in response to an identification that the portion of the activity data matches a mode in the plurality of modes identified as abnormal. Confirmation of the abnormality is requested via a user interface.
摘要翻译： 一种用于识别数据异常的方法，数据处理系统和计算机程序产品。 检索表示从训练数据生成的活动的多个模式的模型。 训练数据包括在一段时间内第一次执行活动的测量。 多个模式中的每一个被标识为正常和异常之一。 接收包括活动的第二次执行的第二多个测量的活动数据。 将活动数据的一部分与模型中的多个模式进行比较。 响应于识别出活动数据的一部分与被识别为异常的多个模式中的模式相匹配的标识来生成第二次活动的异常的通知。 通过用户界面要求确认异常。
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公开(公告)号：US08548203B2
公开(公告)日：2013-10-01
申请号：US12834104
申请日：2010-07-12
申请人： Russell P. Bobbitt , Lei Ding , Quanfu Fan , Sachiko Miyazawa , Sharathchandra U. Pankanti , Yun Zhai
发明人： Russell P. Bobbitt , Lei Ding , Quanfu Fan , Sachiko Miyazawa , Sharathchandra U. Pankanti , Yun Zhai
CPC分类号： G06K9/00335 , G06K9/00771 , G06K9/6224
摘要： Human behavior is determined by sequential event detection by constructing a temporal-event graph with vertices representing adjacent first and second primitive images of a plurality of individual primitive images parsed from a video stream, and also of first and second idle states associated with the respective first and second primitive images. Constructing the graph is a function of an edge set between the adjacent first and second primitive images, and an edge weight set as a function of a discrepancy between computed visual features within regions of interest common to the adjacent first and second primitive images. A human activity event is determined as a function of a shortest distance path of the temporal-event graph vertices.
摘要翻译： 通过构建具有表示从视频流解析的多个单独原始图像的相邻第一和第二原始图像的顶点的时间事件图以及与各自的第一和第二空闲状态相关联的第一和第二空闲状态，通过顺序事件检测来确定人的行为 和第二原始图像。 构造图是在相邻的第一和第二原始图像之间设置的边缘的函数，以及作为相邻第一和第二原始图像共同的感兴趣区域内的计算的视觉特征之间的差异的函数的边缘权重集合。 人类活动事件被确定为时间 - 事件图形顶点的最短距离路径的函数。
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公开(公告)号：US08061603B2
公开(公告)日：2011-11-22
申请号：US12052051
申请日：2008-03-20
申请人： Jonathan H. Connell, II , Myron D. Flickner , Norman Haas , Arun Hampapur , Charles A. Otto , Sharathchandra U. Pankanti
发明人： Jonathan H. Connell, II , Myron D. Flickner , Norman Haas , Arun Hampapur , Charles A. Otto , Sharathchandra U. Pankanti
IPC分类号： G06K15/00
CPC分类号： G07G1/0054
摘要： The present invention provides a solution for controlling checkout throughput. Specifically, under the present invention a set of attributes of an item will be obtained. An analysis of the set of attributes will then be performed to determine whether an inconsistency exists based on a tolerance threshold. Such analysis can include, for example, comparing the weight of the item to its expected weight. This can help determine if a mistake has been made or fraud has been committed. Whether an inconsistency is observed is based on a tolerance threshold. For example, a certain deviation (i.e., the tolerance threshold) from an expected value could be allowed to could be allowed to reduce errors during the checkout process and thereby increase checkout throughput. As such, the present invention allows the tolerance threshold to be tuned based on a desired checkout throughput.
摘要翻译： 本发明提供了一种用于控制检验吞吐量的解决方案。 具体地说，在本发明中，将获得一组物品的属性。 然后将执行对该组属性的分析，以基于公差阈值确定是否存在不一致。 这种分析可以包括例如将物品的重量与其预期重量进行比较。 这可以帮助确定是否发生了错误或已经犯了欺诈。 观察到不一致是基于公差阈值。 例如，可以允许从期望值的一定偏差（即，容限阈值）被允许在结算过程期间减少错误，从而增加结帐吞吐量。 因此，本发明允许基于期望的结算吞吐量来调整公差阈值。
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