Abstract
Product quality is one of the critical issues to be competitive in the global marketplace. In addition, food production companies are strongly required to control high quality of products in their production lines. Contaminations such as metallic, plastic or organic substances are often harmful to human body and should be eliminated completely. Therefore, machine inspections, such as X-ray or fluorescence spectrum methods, are effectively used to eliminate these contaminating substances. However, the final inspections are taken care of by human inspectors to make sure the product quality is kept in the required specifications. Since contaminations are not perfectly eliminated by machine inspections, human inspections are required to cover the un-eliminated ones. However, this is not the only reason why the human inspectors are involved in the quality control. Even though there is no contamination in the products, appearance of products may decrease the quality of the products. For example, most customers would buy Tofu with some air bubble, whereas some customers do not purchase such Tofu which contains many air bubbles, even though air bubble has nothing to do with the taste of Tofu. Therefore, human inspectors review the Tofu package to check the products containing the air bubble, which is hard to be processed by machine inspection. This study proposes image-processing-based air bubble detection method on Tofu packages to inspect the product quality. Based on the results of air bubble detection on the Tofu package, the evaluation is made on each package. The study applied an evaluation criterion based on the experiments. However, the results are not always identical to those by human inspection because of the disagreement of threshold value in evaluation. This chapter presents the image-processing air bubble detection method to determine the quality of Tofu products and discusses the feasibility of this method in comparison with the human inspection results.
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