대한기계학회논문집 (Transactions of the Korean Society of Mechanical Engineers)
- 제17권11호
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- Pages.2711-2722
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- 1993
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- 1225-5963(pISSN)
DOI QR Code
퍼지 클러스터링과 스트링 매칭을 통합한 형상 인식법
Pattern Recognition Method Using Fuzzy Clustering and String Matching
Abstract
Most of the current 2-D object recognition systems are model-based. In such systems, the representation of each of a known set of objects are precompiled and stored in a database of models. Later, they are used to recognize the image of an object in each instance. In this thesis, the approach method for the 2-D object recognition is treating an object boundary as a string of structral units and utilizing string matching to analyze the scenes. To reduce string matching time, models are rebuilt by means of fuzzy c-means clustering algorithm. In this experiments, the image of objects were taken at initial position of a robot from the CCD camera, and the models are consturcted by the proposed algorithm. After that the image of an unknown object is taken by the camera at a random position, and then the unknown object is identified by a comparison between the unknown object and models. Finally, the amount of translation and rotation of object from the initial position is computed.