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Proceedings Paper

Quantitative evaluation method of the bubble structure of sponge cake by using morphology image processing
Author(s): Hironobu Tatebe; Kunihito Kato; Kazuhiko Yamamoto; Yukio Katsuta; Masahiko Nonaka
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Paper Abstract

Now a day, many evaluation methods for the food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that are using for the quality evaluation. An advantage of the image processing is to be able to evaluate objectively. The goal of our research is structure evaluation of sponge cake by using image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner. Because the depth of field of this type scanner is very shallow, the bubble region of the surface has low gray scale values, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. First, input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

Paper Details

Date Published: 6 December 2005
PDF: 8 pages
Proc. SPIE 6051, Optomechatronic Machine Vision, 60511D (6 December 2005); doi: 10.1117/12.664557
Show Author Affiliations
Hironobu Tatebe, Gifu Univ. (Japan)
Kunihito Kato, Gifu Univ. (Japan)
Kazuhiko Yamamoto, Gifu Univ. (Japan)
Yukio Katsuta, Ajinomoto Co., Inc. (Japan)
Masahiko Nonaka, Ajinomoto Co., Inc. (Japan)

Published in SPIE Proceedings Vol. 6051:
Optomechatronic Machine Vision
Kazuhiko Sumi, Editor(s)

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