Paper
13 June 2005 Three-dimensional machine vision utilising optical coherence tomography with a direct read-out CMOS camera
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Abstract
Presented is a comprehensive characterisation of a complementary metal-oxide semiconductor (CMOS) and digital signal processor (DSP) camera, and its implementation as an imaging tool in full-field optical coherence tomography (OCT). The camera operates as a stand-alone imaging device, with the CMOS sensor, analogue-to-digital converter, DSP, digital input/output and random access memory all integrated into one device, autonomous machine vision being its intended application. The 1024x1024 pixels of the CMOS sensor function as a two-dimensional photodiode array, being randomly addressable in space and time and producing a continuous logarithmic voltage proportional to light intensity. Combined with its 120dB logarithmic response range and fast frame rates on small regions of interest, these characteristics allow the camera to be used as a fast full-field detector in carrier based optical metrology. Utilising the camera in an OCT setup, three-dimensional imaging of a typical industrial sample is demonstrated with lateral and axial resolutions of 14μm and 22μm, respectively. By electronically sampling a 64x30 pixel two-dimensional region of interest on the sensor at 235 frames per second as the sample was scanned in depth a volumetric measurement of 875μm x 410μm x 150μm was achieved without electromechanical lateral scanning. The approach presented here offers an inexpensive and versatile alternative to traditional OCT systems and provides the basis for a functional machine vision system suitable for industrial applications.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Patrick Egan, Fereydoun Lakestani, Maurice P. Whelan, and Michael J. Connelly "Three-dimensional machine vision utilising optical coherence tomography with a direct read-out CMOS camera", Proc. SPIE 5856, Optical Measurement Systems for Industrial Inspection IV, (13 June 2005); https://doi.org/10.1117/12.612087
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Cited by 2 scholarly publications.
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KEYWORDS
Cameras

Optical coherence tomography

Digital signal processing

Machine vision

Signal to noise ratio

Sensors

Signal processing

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