[특허]Feature classification using supervised statistical pattern recognition

Feature classification using supervised statistical pattern recognition 원문보기

IPC분류정보
국가/구분	United States(US) Patent 등록
국제특허분류(IPC7판)	G06K-009/68
출원번호	US-0890401 (1992-05-29)
발명자 / 주소	Herbert Thomas F. (Rochester NY)
출원인 / 주소	Eastman Kodak Company (Rochester NY 02)
인용정보	피인용 횟수 : 70 인용 특허 : 0

초록 ▼

Feature classification using a novel supervised statistical pattern recognition approach is described. A tree-like hierarchical decomposition of n-dimensional feature space is created off-line from an image processing system. The hierarchical tree is created through a minimax-type decompositional segregation of n-dimensional feature vectors of different feature classifications within the corresponding feature space. Each cell preferably contains feature vectors of only one feature classification, or is empty, or is of a predefined minimum cell size. Once created, the hierarchical tree is made available to the image processing system for real-time defect classification of features in a static or moving pattern. Each feature is indexed to the classification tree by locating its corresponding feature vector in the appropriate feature space cell as determined by a depth-first search of the hierarchical tree. The smallest leaf node which includes that feature vector provides the statistical information on the vector\s classification.

대표청구항 ▼

A method for generating a statistical classification model from a sample test image having a plurality of features thereon, said statistical classification model for use in real-time feature classification by an image processing system, said method comprising the steps of: (a) imaging said sample test image with said plurality of features thereon to produce a digital image representation thereof; (b) assigning a unique classification to selected features of the same type in said sample test image by referencing said digital image representation; (c) producing an n-element feature vector for each feature classified in said step (b), said n-element feature vectors defining an associated n-dimensional feature space; (d) using said classifications assigned in said step (b) to cluster feature vectors in feature space, said clustering resulting from a minimax search to define a tree-like hierarchical decomposition of n-dimensional feature space based upon said assigned feature classifications; and (e) storing the hierarchically decomposed n-dimensional feature space resulting from said clustering of step (d) for access by said image processing system for real-time feature classification of a new image.

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Feature classification using supervised statistical pattern recognition 원문보기

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Feature classification using supervised statistical pattern recognition 원문보기

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