Determining number of clusters and prototype locations via multi-scale clustering |
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Authors: | Eiji Nakamura Nasser Kehtarnavaz |
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Affiliation: | aDepartment of Information Network Engineering, Aichi Institute of Technology, Toyota, Aichi 4700392, Japan;bDepartment of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA |
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Abstract: | In clustering algorithms, it is usually assumed that the number of clusters is known or given. In the absence of such a priori information, a procedure is needed to find an appropriate number of clusters. This paper presents a clustering algorithm that incorporates a mechanism for finding the appropriate number of clusters as well as the locations of cluster prototypes. This algorithm, called multi-scale clustering, is based on scale-space theory by considering that any prominent data structure ought to survive over many scales. The number of clusters as well as the locations of cluster prototypes are found in an objective manner by defining and using lifetime and drift speed clustering criteria. The outcome of this algorithm does not depend on the initial prototype locations that affect the outcome of many clustering algorithms. As an application of this algorithm, it is used to enhance the Hough transform technique. |
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Keywords: | Nonparametric clustering Multi-scale clustering Cluster validity Number of clusters |
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