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Volume: 33 | Article ID: art00004
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Text Recognition of Cardboard Pharmaceutical Packages by Utilizing Machine Vision
  DOI :  10.2352/ISSN.2470-1173.2021.10.IPAS-235  Published OnlineJanuary 2021
Abstract

In this paper, text recognition of variably curved cardboard pharmaceutical packages is studied from the photometric stereo imaging point-of-view with focus on developing a method for binarizing the expiration date and batch code texts. Adaptive filtering, more specifically Wiener filter, is used together with haze removal algorithm with fusion of LoG-edge detected sub-images resulting an Otsu thresholded binary image of expiration date and batch code texts for future analysis. Some results are presented, and they appear to be promising for text binarization. Successful binarization is crucial in text character segmentation and further automatic reading. Furthermore, some new ideas will be presented that will be used in our future research work.

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Jarmo Koponen, Keijo Haataja, Pekka Toivanen, "Text Recognition of Cardboard Pharmaceutical Packages by Utilizing Machine Visionin Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems XIX,  2021,  pp 235-1 - 235-7,  https://doi.org/10.2352/ISSN.2470-1173.2021.10.IPAS-235

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