Clustering based on scale-space theory /
Clustering is defined as the partitioning of unlabeled data
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| Format: | Thesis Book |
| Language: | English |
| Published: |
[Place of publication not identified] :
[publisher not identified] ;
1997.
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| Subjects: | |
| Online Access: | http://proxy.library.tamu.edu/login?url=http://proquest.umi.com/pqdweb?did=739891291&sid=1&Fmt=2&clientId=2945&RQT=309&VName=PQD |
| Summary: | Clustering is defined as the partitioning of unlabeled data samples into subgroups with similar characteristics. The study of clustering or cluster analysis has been an interdisciplinary research effort and hence numerous clustering algorithms have been reported in the literature. In clustering algorithms, the number of clusters or groupings is usually assumed to be known or given. This dissertation presents a novel clustering algorithm, called muti-scale clustering, by not making such an assumption regarding the number of clusters. The developed algorithm utilizes scalespace theory to form clusters. The use of this theory allows an optimum number of clusters to be found based on survival or existence of clusters over many scale levels. In other words, an optimal number of clusters as well as optimal locations of cluster prototypes and membership values are found in an objective manner by defining lifetime and drift speed clustering criteria. Due to the non-parametric nature of this algorithm, different cluster types can be handled without specifying a norm inducing matrix. The scope of this algorithm is addressed by enhancing the following two cluster-embedded problems (i) the expectation-maximization technique for mixture density estimation in pattern recognition, and (ii) the Hough transform technique for edge detection in image processing. |
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| Item Description: | Vita. "Major Subject: Electrical Engineering". |
| Physical Description: | xi, 113 leaves : illustrations ; 28 cm. Issued also on microfiche from University Microfilms Inc. |
| Bibliography: | Includes bibliographical references: pages 106-112. |