Multi-focusing algorithm for microscopy imagery in assembly line using low-cost camera View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02-13

AUTHORS

Lukas Juočas, Vidas Raudonis, Rytis Maskeliūnas, Robertas Damaševičius, Marcin Woźniak

ABSTRACT

We propose an algorithm to perform multi-focus image fusion and integrate a set of images acquired at different focus settings to a single uniformly focused image for visual inspection in assembly lines. The goal of image fusion is to integrate complementary image multi-view information from standard, low resolution assembly line camera into one new image, the quality of which could not be achieved using other methods such as direct digital photography. Our method is based on the image decomposition into Gaussian pyramids, generation of the Laplacian pyramids, and image reconstruction from the Laplacian pyramids. The main characteristics of the proposed method include good quality of integrated multi-focus image, and suitability for microscopy conveyor applications given movement of objects, different lighting conditions, and positional misalignments. We have evaluated our method using eight image quality metrics yielding good results (best results were obtained using the Tenengrad (TENG) method, reaching an accuracy of 0.982) with a low-cost camera and computationally efficient implementation. More... »

PAGES

1-11

References to SciGraph publications

  • 2013. Object Detection by Simple Fuzzy Classifiers Generated by Boosting in ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING
  • 2009. 3D Shape from Focus and Depth Map Computation Using Steerable Filters in IMAGE ANALYSIS AND RECOGNITION
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    http://scigraph.springernature.com/pub.10.1007/s00170-019-03407-9

    DOI

    http://dx.doi.org/10.1007/s00170-019-03407-9

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