Authors:
José Manuel Fuentes
1
;
Roberto Paredes
1
;
Elena Fulladosa
2
;
María del Mar Giró
2
and
Anna Claret
2
Affiliations:
1
PRHLT Research Center, Universitat Politècnica de València, Valencia, Spain
;
2
IRTA, Food Technology, Girona, Spain
Keyword(s):
Text Transcription, Nutrition, Genetic Algorithms, Image Processing, Convolutional Neural Networks.
Abstract:
Labeling of food products contains key nutritional information, but it is often inaccessible or unclear to users. To alleviate this problem, the application of modern automatic transcription techniques to this field is studied in this paper. This presents a challenge, due to the structural difference of these charts with respect to the usual type of documents for which OCR systems are developed, and also because of the wide visual variability present in this type of labels. For these reasons, a series of algorithms and deep learning models have been developed and applied as pre-processing for the images and post-processing for the transcription obtained, in order to optimize and complement this automatic transcription. With this whole pipeline, we achieve to extract the nutritional information from the pictures in an efficient, complete, accurate and structured way.