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    • 1. 发明授权
    • System and method for image pattern matching using a unified signal transform
    • 使用统一信号变换的图像模式匹配的系统和方法
    • US06807305B2
    • 2004-10-19
    • US09832912
    • 2001-04-10
    • Ram RajagopalLothar WenzelDinesh NairDarren Schmidt
    • Ram RajagopalLothar WenzelDinesh NairDarren Schmidt
    • G06K962
    • G06F17/15G06K9/00496G06K9/52G06K9/522G06K9/6203
    • A system and method for performing pattern matching to locate an instance of one or more of a plurality of template images in a target image. In a preprocessing phase a unified signal transform (UST) is determined from the template images. The UST converts each template image to a generalized frequency domain. The UST is applied at a generalized frequency to each template image to calculate corresponding generalized frequency component values (GFCVs) for each template image. At runtime, the target image is received, and the UST is applied at the generalized frequency to the target image to calculate a corresponding GFCV. The UST may be applied to pixel subsets of the template and target images. A best match is determined between the GFCV of the target image and the GFCVs of each template image. Finally, information indicating the best match template image from the set of template images is output.
    • 一种用于执行图案匹配以定位目标图像中的多个模板图像中的一个或多个的实例的系统和方法。 在预处理阶段,从模板图像确定统一信号变换(UST)。 UST将每个模板图像转换为广义频域。 UST以广义频率应用于每个模板图像,以计算每个模板图像的相应的广义频率分量值(GFCV)。 在运行时,接收目标图像,并以广义频率将UST应用于目标图像,以计算相应的GFCV。 UST可以应用于模板和目标图像的像素子集。 在目标图像的GFCV和每个模板图像的GFCV之间确定最佳匹配。 最后,输出指示模板图像集合中最佳匹配模板图像的信息。
    • 2. 发明授权
    • System and method for signal matching and characterization
    • 用于信号匹配和表征的系统和方法
    • US06963667B2
    • 2005-11-08
    • US09760052
    • 2001-01-12
    • Ram RajagopalLothar WenzelDinesh NairDarren Schmidt
    • Ram RajagopalLothar WenzelDinesh NairDarren Schmidt
    • G06F17/15G06K9/52G06K9/64G06K9/00G06K9/36G06K9/46G06K9/68
    • G06K9/00496G06F17/15G06K9/52G06K9/522G06K9/6203
    • A system and method for selecting a best match of a received input signal from a set of candidate signals, wherein two or more of the candidate signals are uncorrelated. In a preprocessing phase a unified signal transform (UST) is determined from the candidate signals. The UST converts each candidate signal to a generalized frequency domain. The UST is applied at a generalized frequency to each candidate signal to calculate corresponding generalized frequency component values (GFCVs) for each candidate signal. At runtime, the input signal of interest is received, and the UST is applied at the generalized frequency to the input signal of interest to calculate a corresponding GFCV. The best match is determined between the GFCV of the input signal of interest and the GFCVs of each of the set of candidate signals. Finally, information indicating the best match candidate signal from the set of candidate signals is output.
    • 一种用于从一组候选信号中选择接收的输入信号的最佳匹配的系统和方法,其中两个或更多个候选信号是不相关的。 在预处理阶段,从候选信号确定统一信号变换(UST)。 UST将每个候选信号转换成广义频域。 UST以广义频率应用于每个候选信号,以计算每个候选信号的相应的广义频率分量值(GFCV)。 在运行时,接收感兴趣的输入信号,并将UST以广义频率施加到感兴趣的输入信号,以计算相应的GFCV。 在感兴趣的输入信号的GFCV和候选信号组中的每一个的GFCV之间确定最佳匹配。 最后,输出从候选信号组中指示最佳匹配候选信号的信息。
    • 3. 发明授权
    • System and method for curve fitting using randomized techniques
    • 使用随机技术进行曲线拟合的系统和方法
    • US06882958B2
    • 2005-04-19
    • US09894497
    • 2001-06-28
    • Darren SchmidtRam RajagopalLothar WenzelDinesh Nair
    • Darren SchmidtRam RajagopalLothar WenzelDinesh Nair
    • G06F17/17G06F17/00
    • G06F17/17G06K9/6204
    • A system and method for performing a curve fit on a plurality of data points. In an initial phase, a subset Pmax of the plurality of points which represents an optimal curve is determined. This phase is based on a statistical model which dictates that after trying at most Nmin random curves, each connecting a randomly selected two or more points from the input set, one of the curves will pass within a specified radius of the subset Pmax of the input points. The subset Pmax may then be used in the second phase of the method, where a refined curve fit is made by iteratively culling outliers from the subset Pmax with respect to a succession of optimal curves fit to the modified subset Pmax at each iteration. The refined curve fit generates a refined curve, which may be output along with a final culled subset Kfinal of Pmax.
    • 一种用于在多个数据点上执行曲线拟合的系统和方法。 在初始阶段中,确定表示最佳曲线的多个点中的子集P最大值。 该阶段基于统计模型,其指示在尝试最多N分钟随机曲线之后,每个随机曲线连接从输入集合中随机选择的两个或更多个点,其中一个曲线将在指定的 输入点的子集P最大的半径。 然后可以在该方法的第二阶段中使用子集P max,其中通过相对于a的子集P i迭代地淘汰离群值来进行精细曲线拟合 在每次迭代时,优化曲线的连续拟合到修改的子集P最大。 精细曲线拟合产生精细曲线,其可以与最终淘汰的子集K最终一起输出。
    • 4. 发明授权
    • System and method for signal matching and characterization
    • 用于信号匹配和表征的系统和方法
    • US07233700B2
    • 2007-06-19
    • US11105761
    • 2005-04-14
    • Ram RajagopalLothar WenzelDinesh NairDarren Schmidt
    • Ram RajagopalLothar WenzelDinesh NairDarren Schmidt
    • G06K9/62G06K9/36
    • G06K9/00496G06F17/15G06K9/52G06K9/522G06K9/6203
    • A system and method for selecting a best match of a received input signal from a set of candidate signals, wherein two or more of the candidate signals are uncorrelated. In a preprocessing phase a signal transform (UST) is determined from the candidate signals. The UST converts each candidate signal to a generalized frequency domain. The UST is applied at a generalized frequency to each candidate signal to calculate corresponding generalized frequency component values (GFCVs) for each candidate signal. At runtime, the input signal of interest is received, and the UST is applied at the generalized frequency to the input signal of interest to calculate a corresponding GFCV. The best match is determined between the GFCV of the input signal of interest and the GFCVs of each of the set of candidate signals. Finally, information indicating the best match candidate signal from the set of candidate signals is output.
    • 一种用于从一组候选信号中选择接收的输入信号的最佳匹配的系统和方法,其中两个或更多个候选信号是不相关的。 在预处理阶段,从候选信号确定信号变换(UST)。 UST将每个候选信号转换成广义频域。 UST以广义频率应用于每个候选信号,以计算每个候选信号的相应的广义频率分量值(GFCV)。 在运行时,接收感兴趣的输入信号,并将UST以广义频率施加到感兴趣的输入信号,以计算相应的GFCV。 在感兴趣的输入信号的GFCV和候选信号组中的每一个的GFCV之间确定最佳匹配。 最后,输出从候选信号组中指示最佳匹配候选信号的信息。
    • 5. 发明授权
    • System and method for performing edge detection in an image
    • 用于在图像中执行边缘检测的系统和方法
    • US07013047B2
    • 2006-03-14
    • US09894272
    • 2001-06-28
    • Darren SchmidtRam RajagopalLothar WenzelDinesh Nair
    • Darren SchmidtRam RajagopalLothar WenzelDinesh Nair
    • G06K9/48
    • G06K9/4604G06F17/30259G06T7/12G06T7/149
    • A system and method for performing a curve fit on a plurality of data points. In an initial phase, a subset Pmax of the plurality of points which represents an optimal curve is determined. This phase is based on a statistical model which dictates that after trying at most Nmin random curves, each connecting a randomly selected two or more points from the input set, one of the curves will pass within a specified radius of the subset Pmax of the input points. The subset Pmax may then be used in the second phase of the method, where a refined curve fit is made by iteratively culling outliers from the subset Pmax with respect to a succession of optimal curves fit to the modified subset Pmax at each iteration. The refined curve fit generates a refined curve, which may be output along with a final culled subset Kfinal of Pmax.
    • 一种用于在多个数据点上执行曲线拟合的系统和方法。 在初始阶段中,确定表示最佳曲线的多个点中的子集P最大值。 该阶段基于统计模型,其指示在尝试最多N分钟随机曲线之后,每个随机曲线连接从输入集合中随机选择的两个或更多个点,其中一个曲线将在指定的 输入点的子集P最大的半径。 然后可以在该方法的第二阶段中使用子集P max,其中通过相对于a的子集P i迭代地淘汰离群值来进行精细曲线拟合 在每次迭代时,优化曲线的连续拟合到修改的子集P最大。 精细曲线拟合产生精细曲线,其可以与最终淘汰的子集K最终一起输出。
    • 6. 发明申请
    • System and method for signal matching and characterization
    • 用于信号匹配和表征的系统和方法
    • US20050177314A1
    • 2005-08-11
    • US11105761
    • 2005-04-14
    • Ram RajagopalLothar WenzelDinesh NairDarren Schmidt
    • Ram RajagopalLothar WenzelDinesh NairDarren Schmidt
    • G06F17/15G06K9/52G06K9/64G06F7/00G01N33/48G01N33/50G06F17/30G06F19/00
    • G06K9/00496G06F17/15G06K9/52G06K9/522G06K9/6203
    • A system and method for selecting a best match of a received input signal from a set of candidate signals, wherein two or more of the candidate signals are uncorrelated. In a preprocessing phase a signal transform (UST) is determined from the candidate signals. The UST converts each candidate signal to a generalized frequency domain. The UST is applied at a generalized frequency to each candidate signal to calculate corresponding generalized frequency component values (GFCVs) for each candidate signal. At runtime, the input signal of interest is received, and the UST is applied at the generalized frequency to the input signal of interest to calculate a corresponding GFCV. The best match is determined between the GFCV of the input signal of interest and the GFCVs of each of the set of candidate signals. Finally, information indicating the best match candidate signal from the set of candidate signals is output.
    • 一种用于从一组候选信号中选择接收的输入信号的最佳匹配的系统和方法,其中两个或更多个候选信号是不相关的。 在预处理阶段,从候选信号确定信号变换(UST)。 UST将每个候选信号转换成广义频域。 UST以广义频率应用于每个候选信号,以计算每个候选信号的相应的广义频率分量值(GFCV)。 在运行时,接收感兴趣的输入信号,并将UST以广义频率施加到感兴趣的输入信号,以计算相应的GFCV。 在感兴趣的输入信号的GFCV和候选信号组中的每一个的GFCV之间确定最佳匹配。 最后,输出从候选信号组中指示最佳匹配候选信号的信息。
    • 7. 发明授权
    • System and method for color characterization using fuzzy pixel classification with application in color matching and color match location
    • US07046842B2
    • 2006-05-16
    • US09737531
    • 2000-12-13
    • Siming LinDinesh NairDarren Schmidt
    • Siming LinDinesh NairDarren Schmidt
    • G06K9/00
    • G06K9/3241G06K9/4652G06K9/6293G06T7/001G06T2207/10024G06T2207/30141
    • A system and method for measuring the similarity of multiple-color images and for locating regions of a target image having color information that matches, at least to a degree, the color information of a template image. A color characterization method operates to characterize the colors of an image and to measure the similarity between multiple-color images. For each image pixel, the method determines a color category or bin for the respective pixel based on HSI values of the respective pixel, wherein the color category is one of a plurality of possible color categories in HSI color space. In various embodiments, the weight of the pixel may be fractionally distributed across a plurality of color categories, e.g., as determined by applying fuzzy pixel classification with a fuzzy membership function. The percentage of pixels assigned to each category is then determined. The percentage of pixels in each color category is then used as a color feature vector to represent the color information of the color image. A quantitative measurement of the color similarity between color images is then computed based on the distance between their color feature vectors. Once the color information of a template image has been characterized, a target image may be searched in order to locate regions within the target image having matching color information. In one embodiment, a coarse-to-fine heuristic may be utilized, in which multiple search stages of decreasing granularity are performed. A first-stage search may operate to identify a list of candidate match regions based on the city-block distance of the color feature vector computed using a sub-sampling scheme. These candidate match regions may then be examined in further detail in order to determine final matches.