The method to read nutrient quantity in guideline daily amounts label by image processing

Abstract

Guideline Daily Amounts (GDAs) provides guideline of nutrition information to help consumers known the context of their overall diet. In this paper, we proposed a method to read nutrition information of GDAs on a food label by image processing. This method consists of three steps: label extraction, number segmentation, and number recognition. First, GDAs label is captured by a camera. Otsu's threshold including with a constants threshold of color level is used to define an area of the label. Second, four numbers of nutrition in the GDAs label is segmented based on an area divider algorithm. Third, the number is recognized by the Neural Network technique. Finally, quantity of each nutrition in a label is read. To evaluate performance of the proposed method, forty images are tested. A GDAs label consists of four nutrition. Number zero to nine in the label is classified. Total number is 407 numbers. 302 numbers are classified correctly. The accuracy is 74.20%. The experimental results is satisfactory.