Kunlachat Seniwong Na Ayutthaya ¹, Pradit Mittrapiyanuruk ², Pakorn Kaewtrakulpong ³

Affiliations
1 Institute of Field Robotics, King Mongkut’s University of Technology Thonburi 126 Pracha-utid Rd., Bangmod, Tungkaru, Bangkok - 10140, TH
2 Department of Mathematics, Faculty of Science, Srinakharinwirot University 114 Sukhumvit 23, Bangkok - 10110, TH
3 Department of Control System and Instrumentation Engineering, Faculty of Engineering, King Mongkut’s University of Technology Thonburi 126 Pracha-utid Rd., Bangmod, Tungkaru, Bangkok - 10140, TH

Abstract

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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Berlian Akbar Yon Agusta ¹, Pradit Mittrapiyanuruk ², Pakorn Kaewtrakulpong ³

Affiliations
1 School of Electrical Engineering and Informatics, InstitutTeknologi Bandung, ID
2 Department of Mathematics, Faculty of Science, Srinakharinwirot University, 114 Sukhumvit 23, Bangkok – 10110, TH
3 Department of Control System and Instrumentation Engineering, King Mongkut’s University of Technology, Thonburi 126 Pracha-utid Road, Bangmod, Tungkaru, Bangkok – 10140, TH

Abstract

In this work, we present a people counting algorithm using depth images acquired from a KINECT camera that is installed vertically, i.e., pointing toward the floor. Our proposed algorithm is referred to as Field seeding algorithm. The key idea is that first a set of local minimum values are detected from several spatially distributed seed locations. Then, the peoplehead blobs are detected from the binary images generated with regard to the threshold values derived from the local minimum values. The recall, accuracy and F-score of our algorithm are comparable to the current state-of-the-art people counting using KINECT, i.e. Water Filling. However, the main advantage over the previous method is that our algorithm operates deterministically, i.e., no any random number generating function is used.

Keywords

Depth Image, Head Detection, People Counting, Vertical Kinect.

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Kunlachat Seniwong Na Ayutthaya ¹, Pradit Mittrapiyanuruk ², Pakorn Kaewtrakulpong ³

Affiliations
1 Institute of Field Robotics, King Mongkut’s University of Technology Thonburi, 126 Pracha-utid Road, Bangmod, Tungkaru, Bangkok – 10140, TH
2 Department of Mathematics, Srinakharinwirot University, 114 Sukhumvit 23, Bangkok – 10110, TH
3 Department of Control System and Instrumentation Engineering, King Mongkut’s University of Technology, Thonburi 126 Pracha-utid Road, Bangmod, Tungkaru,Bangkok – 10140, TH

Abstract

In this paper, we present a single-lens based imaging system that its focal length can be adjusted by using Liquid Crystal Spatial Light Modulator (LC-SLM). The SLM is placed at the aperture stop of the imaging system to work as a Phase Mask (PM) that modifies the light wavefront passing the exit pupil. By changing the pixel-based PM pattern that sends to the SLM, the focal length of the imaging system can be varied in the same spirit as conventional mechanical-zoom lenses. We demonstrate a proof-of-concept system for high magnification industrial inspection applications in a laboratory setup. We show the results that the focal length of the system is adjustable within the range ±2.0mm.

Keywords

Autofocus, Adaptive Focal Length, Liquid Crystal, Phase Mask, Spatial Light Modulator, Wavefront Modification.

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