Abstract
This paper proposes a method for an automatic classification system of surface mount devices (SMDs) focused on the periodicity of leads. Automatic classification methods for the type of SMD are required as preprocessing for mounting SMDs in chip mounters. Due to the variations of connector parts, the previous method has a low accuracy rate. This paper presents a classification method for multiple types of SMDs by using Higher-order Local AutoCorrelation (HLAC) features from the power spectrum of an SMD image. Support Vector Machine (SVM) automatically classifies connector parts including the periodicity of leads by using HLAC features from a spectrum. The experimental results show that the proposed method improved the accuracy rate of the connectors (115 samples) from 40.0[%] to 91.3[%]. For all kinds of parts (748 samples), the accuracy rate was improved from 89.2[%] to 96.0[%].
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