| Summary: | 碩士 === 國立交通大學 === 工業工程研究所 === 84 === This thesis presents techniques for classifying workpieces
using the revised simplified skeleton. The proposed revised
simplified skeleton extends the firepropagation rules of the
simplified skeleton (Wu and Chen 1992). The revised simplified
skeleton, as a global shape descriptor, not only captures the
globalshape features, including the skeletal feature and acute
shapecorners, but alsogreatly simplifies skeleton''s complexity.
As a result, the revised simplifiedskeleton is an ideal shape
descriptor for applications such as workpiece class-ification.
The proposed classification technique is a two-phase procedure.
In the first phase, workpieces are grouped coarsely according to
the contours oftheir projections. The coarse classification is
performed by similarity matchingon the representative ring code
derived from each contour. In the second phase,workpieces within
the same group are classified in a refinement fasion accordingto
the revised simplified skeletons of their contours. In the
refining classification, the derived revised simplified skeleton
is converted first to a three structureand then to a vector
representation. The vector representation will be read asan
input by a back-propagation neural network.Based on the results
of the neuralnetwork, workpieces within the same groupare
further classified into families ina three-level hierarchical
structure.
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