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    • 3. 发明授权
    • Ambiguity reduction for image alignment applications
    • 图像校准应用的模糊度降低
    • US09430457B2
    • 2016-08-30
    • US14582321
    • 2014-12-24
    • Xerox Corporation
    • Martin S. Maltz
    • G06F17/24H04N1/387
    • G06F17/243G06F17/248H04N1/3873H04N2201/0081
    • According to exemplary systems and methods, a template is partitioned into blocks using an image processor. An image is scanned using an optical scanner. The image is aligned to the template. Image features are matched with template features in the blocks of the template. Displacement vectors are identified for differences of the image features from the template features. Normalized cross correlation (NCC) is determined between blocks of the image and each block of the template using the image processor. Peaks in the NCC are identified. A displacement vector is selected for a peak with highest NCC for each the block of the template. Ambiguous template features are identified in the image based on the displacement vector. Blocks are iteratively combined and NCC determined to remove the ambiguous template features.
    • 根据示例性系统和方法,使用图像处理器将模板分割成块。 使用光学扫描仪扫描图像。 图像与模板对齐。 图像特征与模板块中的模板特征相匹配。 识别图像特征与模板特征的差异的位移向量。 使用图像处理器在图像的块和模板的每个块之间确定归一化互相关(NCC)。 确定NCC中的峰。 为模板的每个块选择具有最高NCC的峰的位移矢量。 基于位移矢量在图像中识别不明确的模板特征。 块被迭代组合,并且确定NCC以消除模糊模板特征。
    • 7. 发明申请
    • AMBIGUITY REDUCTION FOR IMAGE ALIGNMENT APPLICATIONS
    • 图像对准应用的缩减
    • US20160188559A1
    • 2016-06-30
    • US14582321
    • 2014-12-24
    • Xerox Corporation
    • Martin S. Maltz
    • G06F17/24H04N1/387
    • G06F17/243G06F17/248H04N1/3873H04N2201/0081
    • According to exemplary systems and methods, a template is partitioned into blocks using an image processor. An image is scanned using an optical scanner. The image is aligned to the template. Image features are matched with template features in the blocks of the template. Displacement vectors are identified for differences of the image features from the template features. Normalized cross correlation (NCC) is determined between blocks of the image and each block of the template using the image processor. Peaks in the NCC are identified. A displacement vector is selected for a peak with highest NCC for each the block of the template. Ambiguous template features are identified in the image based on the displacement vector. Blocks are iteratively combined and NCC determined to remove the ambiguous template features.
    • 根据示例性系统和方法,使用图像处理器将模板分割成块。 使用光学扫描仪扫描图像。 图像与模板对齐。 图像特征与模板块中的模板特征相匹配。 识别图像特征与模板特征的差异的位移向量。 使用图像处理器在图像的块和模板的每个块之间确定归一化互相关(NCC)。 确定NCC中的峰。 为模板的每个块选择具有最高NCC的峰的位移矢量。 基于位移矢量在图像中识别不明确的模板特征。 块被迭代组合,并且确定NCC以消除模糊模板特征。