Performance prediction of optical image stabilizer using SVM for shaker-free production line

Abstract

Recent smartphones adapt the camera module with optical image stabilizer(OIS) to enhance imaging quality in handshaking conditions. However, compared to the non-OIS camera module, the cost for implementing the OIS module is still high. One reason is that the production line for the OIS camera module requires a highly precise shaker table in final test process, which increases the unit cost of the production. In this paper, we propose a framework for the OIS quality prediction that is trained with the support vector machine and following module characterizing features : noise spectral density of gyroscope, optically measured linearity and cross-axis movement of hall and actuator. The classifier was tested on an actual production line and resulted in 88% accuracy of recall rate.