Invention Application
US20060078219A1 Image viewing and method for generating filters for filtering image feaures according to their orientation
审中-公开
用于生成过滤器的图像查看和方法,用于根据其方向过滤图像特征
- Patent Title: Image viewing and method for generating filters for filtering image feaures according to their orientation
- Patent Title (中): 用于生成过滤器的图像查看和方法,用于根据其方向过滤图像特征
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Application No.: US10542897Application Date: 2004-01-16
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Publication No.: US20060078219A1Publication Date: 2006-04-13
- Inventor: Raoul Florent , Sherif Makram-Ebeid
- Applicant: Raoul Florent , Sherif Makram-Ebeid
- Applicant Address: NL BA Eindhoven 5621
- Assignee: Koninklijke Philips Electronics N.V.
- Current Assignee: Koninklijke Philips Electronics N.V.
- Current Assignee Address: NL BA Eindhoven 5621
- Priority: EP03290162.1 20030122
- International Application: PCT/IB04/00138 WO 20040116
- Main IPC: G06K9/40
- IPC: G06K9/40

Abstract:
Image processing system for generating a multidimensional adaptive oriented filter to process image data in a number d of dimensions, comprising product means for producing weighted scalar coefficients [W1(r), . . . Wi(r), . . . Wd(r)] of a number d of vectors of an oriented basis of vectors by a number n of local vectors related to each point; combining means (Π) for producing a set of one-scalar weight coefficients [W(r)] from the combination of the weighted scalar products; and filtering means (g) for producing filtered image data [g(x)] from the combination of the image data [I(x)] with the one-scalar weight coefficients [W(r)]. The system further comprises a direction estimator (10) for providing, at each image point, an oriented orthogonal basis of a number d of vectors (e1, . . . ei, . . . ed); a site generator (20) for providing n site vectors of a local vector support; and product means for computing d scalar products of vectors of the orthogonal basis by each of the n site vectors. This system may also comprise means for providing weighting means for the scalar products through scalar functions. The filtering means may comprise a weighted normalized sum of the image data by the one-scalar weight coefficients [W(r)].
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