DocumentCode
1972813
Title
Recognition and classification of numerical labels using digital image processing techniques
Author
Arrighi, T. ; Rojas, J.E. ; Soto, J.C. ; Madrigal, C.A. ; Londoño, J.A.
Author_Institution
Univ. de Antioquia, Antioquia, Colombia
fYear
2012
fDate
12-14 Sept. 2012
Firstpage
252
Lastpage
260
Abstract
This article describes the methodology used for the automatic classification of finished products at Familia Sancela Company, Medellin plant, by visual recognition of numeric codes labels, printed on their packaging, before the stowage and storage procedures. Based on the morphology and package design and techniques using digital image processing and artificial vision, it seeks to graphically detect a numeric label that encodes the product, whose characters are framed in a box. For this, an image preprocessing by thresholding, are the outlines of the image and using the polynomial approximation method detected the rectangle that frames the numerical code, this region is applied an orientation correction algorithm, it is a segmentation of each digit in individual images and finally apply the algorithm of Optical Character Recognition (OCR), which determines the value of the character by comparing the Euclidean distances between the projection of the character and the established databases. The implementation of this automation results in an optimization in the packaging procedure as well as decrease of time, costs and errors. All processing is done using the computer vision library, OpenCV and cvBlobsLib, in the development platform Microsoft Visual Studio C + + 2010.
Keywords
computer vision; image classification; image segmentation; optical character recognition; polynomial approximation; Euclidean distances; Microsoft Visual Studio C + + 2010; OCR; OpenCV computer vision library; artificial vision; automatic classification; cvBlobsLib; digital image processing techniques; image classification; image preprocessing; image thresholding; numeric codes labels; optical character recognition; orientation correction algorithm; package design; polynomial approximation; storage procedures; stowage procedures; visual recognition; Digital images; Educational institutions; Image resolution; Image segmentation; Licenses; Optical character recognition software; Visualization; Binarization; Boundary; Detection; Digital; Image; OCR; OTSU; Prosecution; ROI; Segmentation; Threshold;
fLanguage
English
Publisher
ieee
Conference_Titel
Image, Signal Processing, and Artificial Vision (STSIVA), 2012 XVII Symposium of
Conference_Location
Antioquia
Print_ISBN
978-1-4673-2759-6
Type
conf
DOI
10.1109/STSIVA.2012.6340592
Filename
6340592
Link To Document