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Home arrow News arrow Best Paper Award - SPIE Electronic Imaging, San Francisco 2014
Best Paper Award - SPIE Electronic Imaging, San Francisco 2014

21.2.2014

We are pleased to announce that Mgr. Svorad Štolc, PhD. was awarded with Best Paper Award, given for the presentation of his work Depth and all-in-focus images obtained by multi-line-scan light-field approach, on international Conference IS&T / SPIE International Conference on Image Processing: Machine Vision Applications VII, San Francisco, USA, February 2-6, 2014.

ŠTOLC, S. - HUBER-MÖRK, R. - HOLLÄNDER, B. - SOUKUP, D.: Depth and all-in-focus images obtained by multi-linescan light-field approach. To appear in: Proc. of IS&T / SPIE Electronic Imaging - Image Processing: Machine Vision Applications VII, February 2014. 

Abstract

We present a light-field multi-line-scan image acquisition and processing system intended for the 2.5/3-D inspection of fine surface structures, such as small parts, security print, etc. in an industrial environment. The system consists of an area-scan camera, that allows for a small number of sensor lines to be extracted at high frame rates, and a mechanism for transporting the inspected object at a constant speed. During the acquisition, the object is moved orthogonally to the camera's optical axis as well as the orientation of the sensor lines. In each time step, a predefined subset of lines is read out from the sensor and stored. Afterward, by collecting all corresponding lines acquired over time, a 3-D light field is generated, which consists of multiple views of the object observed from different viewing angles while transported w.r.t. the acquisition device. This structure allows for the construction of so-called epipolar plane images (EPIs) and subsequent EPI-based analysis in order to achieve two main goals: (i) the reliable estimation of a dense depth model and (ii) the construction of an all-in-focus intensity image. Beside specifics of our hardware setup, we also provide a detailed description of algorithmic solutions for the mentioned tasks. Two alternative methods for EPI-based analysis are compared based on artificial and real-world data

Best Paper Award Certificate_Stolc
 
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