Recognizing shipbuilding parts using artificial neural networks and Fourier descriptors

被引：33
|
作者：
Sanders, D. A. [1 ]
机构：
[1] Univ Portsmouth, Dept Mech & Design Engn, Portsmouth PO1 3DJ, Hants, England
来源：
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE | 2009年 / 223卷 / 03期
关键词：
pattern recognition; object recognition; shipbuilding; neural network; Fourier descriptor; INVARIANT PATTERN-RECOGNITION;
D O I：
10.1243/09544054JEM1382
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
A pattern recognition system is described for recognizing shipbuilding parts using artificial neural networks and Fourier descriptors. The system uses shape contour information that is invariant of size, translation, and rotation. Fourier descriptors provide information, and the neural networks make decisions about the shapes. A brief review of the current state of the art is included, and results from testing show that the system distinguished between various shapes and proved to be a valid approach.
引用
收藏
页码：337 / 342
页数：6
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