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http://dx.doi.org/10.13067/JKIECS.2015.10.2.267

Optimal Structures of a Neural Network Based on OpenCV for a Golf Ball Recognition  

Kim, Kang-Chul (전남대학교 전기전자통신컴퓨터공학부)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.10, no.2, 2015 , pp. 267-274 More about this Journal
Abstract
In this paper the optimal structure of a neural network based on OpenCV for a golf ball recognition and the intensity of ROI(Region Of Interest) are calculated. The system is composed of preprocess, image processing and machine learning, and a learning model is obtained by multi-layer perceptron using the inputs of 7 Hu's invariant moments, box ration extracted by vertical and horizontal length or ${\pi}$ calculated by area of ROI. Simulation results show that optimal numbers of hidden layer and the node of neuron are selected to 2 and 9 respectively considering the recognition rate and running time, and optimal intensity of ROI is selected to 200.
Keywords
Neural network; OpenCV; Optimal Structure; Pattern Recognition;
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Times Cited By KSCI : 2  (Citation Analysis)
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