Study on classification method of flat springs based on machine vision

doi:10.16731/j.cnki.1671-3133.2017.03.022

Abstract

Abstract: In order to realize the automatic classification of flat springs a new classification method based on machine vision is proposed.And the distribution vectors of black pixel is extracted as the feature parameter vector.Then,the SVMs DDAG method is used to classify the different types of flat springs,and the test samples of flat spring are classified into different types.The result shows that this classification method is so efficient and accurate that can meet the requirements of the flat spring automatic classification.

Key words: flat spring classification, machine vision, feature extraction, DDAG SVMs

CLC Number:

TP391

Chen Peng, Zhang Aimei, Zhang Qiang, Wang Huamin. Study on classification method of flat springs based on machine vision[J]. Modern Manufacturing Engineering, 2017, 438(3): 126-129.

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Study on classification method of flat springs based on machine vision

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