Feature regulation for hierarchical decision learning
    21.
    发明授权
    Feature regulation for hierarchical decision learning 有权
    层次决策学习的特征规范

    公开(公告)号:US07233931B2

    公开(公告)日:2007-06-19

    申请号:US10746169

    申请日:2003-12-26

    IPC分类号: G06F15/18 G06N3/08 G06K9/64

    摘要: A feature regulation application method for hierarchical decision learning systems receives feature regulation training data and invokes a plurality of hierarchical decision learning to create feature subset information output. The method receives learning data and uses the feature subset information and the learning data to create feature subset learning data output. The hierarchical decision learning method uses the feature subset learning data to create hierarchical decision output. The feature regulation method also outputs feature ranking information that can be used to create hierarchical decision output. The invention provides a computationally feasible method for feature selection that considers the hierarchical decision learning systems used for decision making.

    摘要翻译: 用于分层决策学习系统的特征调节应用方法接收特征调节训练数据,并且调用多个分层决策学习来创建特征子集信息输出。 该方法接收学习数据,并使用特征子集信息和学习数据来创建特征子集学习数据输出。 层次决策学习方法使用特征子集学习数据来创建分层决策输出。 特征调节方法还输出可用于创建分层决策输出的特征排序信息。 本发明提供了一种考虑用于决策的层次决策学习系统的特征选择的计算可行方法。

    Fast invariant pattern search
    22.
    发明授权
    Fast invariant pattern search 有权
    快速不变图案搜索

    公开(公告)号:US07149357B2

    公开(公告)日:2006-12-12

    申请号:US10302466

    申请日:2002-11-22

    IPC分类号: G06K9/62

    CPC分类号: G06K9/6203 G06K9/4647

    摘要: Rotation and scale invariant profiles are generated for matching to a pattern template using a fast regular shaped pattern construction method. The invention achieves rotation invariant matching, rotation and scale invariant matching, and/or scale invariant matching. Invariant profiles are used to perform fast rotation, rotation and scale, or scale invariant search for initial detection of match candidates. The rotation invariant contours of this invention approximate circular contours through use of regular shaped patterns such as octagon or multiple rotated octagons. Rotation invariant search does not depend on rotation angles and is very fast.

    摘要翻译: 生成旋转和尺度不变轮廓,以使用快速规则形状的图案构造方法与模式模板匹配。 本发明实现旋转不变匹配,旋转和尺度不变匹配,和/或尺度不变匹配。 不变轮廓用于执行快速旋转,旋转和缩放,或缩放不变式搜索以初始检测匹配候选。 本发明的旋转不变轮廓通过使用诸如八边形或多个旋转八边形的规则形状图案来近似圆形轮廓。 旋转不变量搜索不依赖于旋转角度并且非常快。

    Fast invariant matching using template decomposition and synthesis
    23.
    发明授权
    Fast invariant matching using template decomposition and synthesis 有权
    使用模板分解和合成的快速不变匹配

    公开(公告)号:US07110603B2

    公开(公告)日:2006-09-19

    申请号:US10419913

    申请日:2003-04-16

    IPC分类号: G06K9/62 G06K9/00 G06K9/46

    CPC分类号: G06K9/4647 G06K9/6203

    摘要: A fast matching method performs pattern decomposition and synthesis learning to create a pattern search recipe that is used by an invariant pattern search and synthesis method to generate the match result. The pattern search recipe includes template component invariant profiles, component weights, and allowable partial pattern configurations. The invariant matching method supports partial pattern match. This invention decomposes a template into multiple compact shaped components and performs search using separate rotation and scale invariant profiles for each component. It then synthesizes the search results for the complete template or partial template using the component search results.

    摘要翻译: 快速匹配方法执行模式分解和合成学习,以创建由不变图案搜索和合成方法用于生成匹配结果的模式搜索配方。 模式搜索配方包括模板组件不变轮廓,组件权重和可允许的部分模式配置。 不变匹配方法支持部分模式匹配。 本发明将模板分解为多个紧凑形状的组件,并且使用针对每个组件的单独的旋转和尺度不变轮廓来执行搜索。 然后使用组件搜索结果合成完整模板或部分模板的搜索结果。

    Fast regular shaped pattern searching
    24.
    发明授权
    Fast regular shaped pattern searching 有权
    快速规则形状搜索

    公开(公告)号:US07054492B2

    公开(公告)日:2006-05-30

    申请号:US10255016

    申请日:2002-09-24

    IPC分类号: G06K9/62

    CPC分类号: G06K9/6203 G06K9/4604

    摘要: An accumulation method for fast pattern search can accurately locate regular shaped patterns of interest. The method can be used for invariant search to match patterns of interest in images where the searched pattern varies in size or orientation or aspect ratio, when pattern appearance is degraded, and even when the pattern is partially occluded, where the searched image is large, multidimensional, or very high resolution, or where the pattern size is large. The computation requirement is independent of the size of the pattern region.

    摘要翻译: 用于快速图案搜索的累积方法可以准确地定位感兴趣的规则形状图案。 该方法可以用于不变搜索以匹配图像中所关注的图案,其中搜索的图案在尺寸或取向或纵横比上变化,当图案外观劣化时,甚至当图案被部分遮挡时,搜索图像大, 多维或非常高的分辨率,或者图案尺寸大的地方。 计算要求与图案区域的大小无关。

    Method for detection optimization in image-based decision systems

    公开(公告)号:US07031529B2

    公开(公告)日:2006-04-18

    申请号:US10178166

    申请日:2002-06-24

    IPC分类号: G06K9/68

    摘要: A systematic way of linking structure constraints of components of a common object and checking and resolving their inconsistency is used to improve detection results in image-based decision systems. A multilevel Chain-And-Tree (CAT) model is used to direct processing using both forward and backward scans through the related components. Since components occur as parts of an object, the context (relational structure) in which the component appears can be used to reduce noise and variation affects. In the method, object knowledge is translated into constraints between components. The constraints are used to enhance feature detection, defect detection, and measurement accuracy and consistency.

    Structure-guided automatic learning for image feature enhancement
    26.
    发明授权
    Structure-guided automatic learning for image feature enhancement 有权
    结构引导自动学习图像特征增强

    公开(公告)号:US06507675B1

    公开(公告)日:2003-01-14

    申请号:US09815466

    申请日:2001-03-23

    IPC分类号: G06K940

    摘要: A structure-guided automatic learning system for image feature enhancement uses a learning image together with an application domain structure and detection target specification to produce a feature enhancement image processing recipe. An enhancement goodness measure is used to select between alternatives in the learning process. The feature enhancement recipe is used in an application module to process input images and produce a feature enhanced image output. Calipers are used for application domain structure and detection target specification. To unify the processing steps for all caliper specifications, a non-directional box caliper defined region such as a circle caliper or an arc caliper or other connected structures can be converted into a directional box caliper defined region so that a directional box caliper based feature enhancement method can be applied. The process can be inverted to convert a converted directional box caliper region back to the original format.

    摘要翻译: 用于图像特征增强的结构引导自动学习系统使用学习图像以及应用领域结构和检测目标规范来产生特征增强图像处理配方。 增强善良度量被用于在学习过程中选择替代方案。 特征增强配方在应用模块中用于处理输入图像并产生特征增强图像输出。 卡尺用于应用领域结构和检测目标规范。 为了统一所有卡尺规格的加工步骤,可以将诸如圆形卡尺或弧形卡尺或其他连接结构的非方向盒卡尺定义的区域转换成定向盒卡尺规定的区域,以便基于方向盒卡尺的特征增强 方法可以应用。 该过程可以反转,以将转换的方向盒卡尺区域转换回原始格式。

    Method and apparatus for robust biological specimen classification
    27.
    发明授权
    Method and apparatus for robust biological specimen classification 失效
    强大的生物标本分类方法和装置

    公开(公告)号:US5740269A

    公开(公告)日:1998-04-14

    申请号:US309209

    申请日:1994-09-20

    IPC分类号: G06K9/00

    CPC分类号: G06K9/00127

    摘要: A robust biological specimen classifier. An automated microscopy system obtains features from an image of a biological specimen slide. A computer system in the automated microscopy system computes feature variations. Clusters are created that comprise samples of similar characteristics. A cluster membership generator generates membership values for each cluster. Classifiers specialized to certain feature sets are used to provide independent outputs. These outputs are offset and biased by the output of the membership generator. The output of the adjusted classification values are summed to create a slide score output.

    摘要翻译: 强大的生物样本分类器。 自动显微镜系统从生物标本载玻片的图像中获得特征。 自动显微镜系统中的计算机系统计算特征变化。 创建了包含类似特征样本的集群。 集群成员资格生成器为每个集群生成成员资格值。 专门用于某些特征集的分类器用于提供独立的输出。 这些输出由成员生成器的输出偏移和偏移。 将调整后的分类值的输出相加以创建幻灯片分数输出。

    Method and apparatus for integrating an automated system to a laboratory
    28.
    发明授权
    Method and apparatus for integrating an automated system to a laboratory 失效
    将自动化系统整合到实验室的方法和装置

    公开(公告)号:US5619428A

    公开(公告)日:1997-04-08

    申请号:US455388

    申请日:1995-05-31

    IPC分类号: G01B9/04 G01N1/31 G02B21/36

    CPC分类号: G01N1/312

    摘要: An automated biological screening system obtains biological and procedural data from a slide set of a selected clinical laboratory. The integration system tests the data on standardized criteria and passes and fails the data in selected categories. The results of the assessment are used to make process adjustment recommendations based on the results of a laboratory process adjustment procedure. Assessment and adjustment may continue until data from a slide set from the selected clinical laboratory passes in each category. The integration system then sets up, calibrates and installs the automated biological screening system. During operation, the integration system continuously monitors biological data generated by the automated biological screening system. The biological data may also be stored in a central product/service database for additional monitoring. The integration system also serves as an objective standard for reviewing and improving laboratory practices.

    摘要翻译: 自动生物筛选系统从选定的临床实验室的幻灯片中获得生物学和程序性数据。 集成系统对标准化标准的数据进行测试,并对所选类别的数据进行传递和失败。 评估结果用于根据实验室过程调整程序的结果制定过程调整建议。 评估和调整可以继续,直到来自所选临床实验室的幻灯片的数据在每个类别中通过。 整合系统建立,校准和安装自动化生物筛选系统。 在运行过程中,集成系统会持续监控自动化生物筛选系统产生的生物数据。 生物数据也可以存储在中央产品/服务数据库中以用于附加监控。 整合系统也是检查和改进实验室实践的客观标准。

    Teachable object contour mapping for biology image region partition
    29.
    发明授权
    Teachable object contour mapping for biology image region partition 有权
    用于生物图像区域划分的可对象轮廓映射

    公开(公告)号:US09122951B2

    公开(公告)日:2015-09-01

    申请号:US12925874

    申请日:2010-11-01

    IPC分类号: G06K9/34 G06K9/00

    CPC分类号: G06K9/342 G06K9/0014

    摘要: A teachable object contour mapping method for region partition receives an object boundary and a teaching image. An object contour mapping recipe creation is performed using the object boundary and the teaching image to generate object contour mapping recipe output. An object contour mapping is applied to an application image using the object contour mapping recipe and the application image to generate object contour map output. An object region partition using the object contour map to generate object region partition output. An updateable object contour mapping method receives a contour mapping recipe and a validation image. An object contour mapping is performed using the object contour mapping recipe and the validation image to generate validation contour map output. An object region partition receives a region mask to generate validation object region partition output. A boundary correction is performed using the validation object region partition to generate corrected object boundary output. An update contour mapping is performed using the corrected object boundary, the validation image and the contour mapping recipe to generate updated contour mapping recipe output.

    摘要翻译: 区域分区的可教对象轮廓映射方法接收对象边界和教学图像。 使用对象边界和教学图像执行对象轮廓映射配方创建,以生成对象轮廓映射配方输出。 使用对象轮廓映射配方和应用图像将对象轮廓映射应用于应用图像以生成对象轮廓图输出。 对象区域分区使用对象轮廓图生成对象区域分区输出。 可更新的对象轮廓映射方法接收轮廓映射配方和验证图像。 使用对象轮廓映射配方和验证图像执行对象轮廓映射以生成验证轮廓图输出。 对象区域分区接收区域掩码以生成验证对象区域分区输出。 使用验证对象区域分区执行边界校正,以生成校正对象边界输出。 使用校正的对象边界,验证图像和轮廓映射配方来执行更新轮廓映射以生成更新的轮廓映射配方输出。

    Method of directed pattern enhancement for flexible recognition
    30.
    发明申请
    Method of directed pattern enhancement for flexible recognition 有权
    用于灵活识别的定向图案增强方法

    公开(公告)号:US20100092075A1

    公开(公告)日:2010-04-15

    申请号:US12587157

    申请日:2009-10-02

    IPC分类号: G06K9/62 G06K9/40 G06K9/48

    摘要: A directed pattern enhancement method receives a learning image and pattern enhancement directive. Pattern enhancement learning is performed using the learning image and the pattern enhancement directive to generate pattern enhancement recipe. An application image is received and a pattern enhancement application is performed using the application image and the pattern enhancement recipe to generate pattern enhanced image. A recognition thresholding is performed using the pattern enhanced image to generate recognition result. The pattern enhancement directive consists of background directive, patterns to enhance directive, and patterns to suppress directive. An update learning method performs pattern enhancement progressive update learning.

    摘要翻译: 定向图案增强方法接收学习图像和图案增强指令。 使用学习图像和图案增强指令执行图案增强学习以产生图案增强配方。 接收应用图像,并且使用应用图像和图案增强配方来执行图案增强应用以生成图案增强图像。 使用图案增强图像执行识别阈值以产生识别结果。 模式增强指令包括背景指令,增强指令的模式和抑制指令的模式。 更新学习方法执行模式增强渐进式更新学习。