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In Hard Disk Drive (HDD) slider fabrication process, the slider bar auditing is required to verify if the slider bars in the tray are sorted correctly as indicated by the serial numbers printed on sliders. In this paper, we present a machine vision system for automated reading of the serial numbers. Since the sizes of slider bars are very small, an imaging system (CCD camera) with high magnification lens is usually exploited to acquire the slide bar images. For such high magnification vision system, an autofocus module is indispensable. Unlike conventional autofocus modules which perform using mechanical zoom lens, we develop an autofocus module based on Spatial Light Modulator (SLM) where the SLM will act as phase mask filter for focus adjustment. The key contribution of our work is that we perform non-mechanical autofocus approach by adjusting the pixel-based phase mask pattern sending through the SLM. The main advantage of our system is that there is no macromechanical movement part involved in Z-axis focus adjustment. We propose a machine vision algorithm that consists of 3 major steps including coarse localization of slider bar, Autofocus and optical character recognition (OCR). To our best knowledge, our developed system is the first system that uses the SLM based autofocus in machine vision for HDD slider manufacturing. From the experiment, our system can accomplish the task with very high accuracy. By using our system, we can improve the machine vision applications by replacing conventional mechanical zoom lens based autofocus modules that generally cause machine vibrations and increasing maintenance costs related to mechanical movement issues.

Keywords

Autofocusing, HDD Slider Bar, Slider Bar Auditing, Spatial Light Modulator
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