Implementation of Maximally Stable Extremal Region for Text Segmentation on Food Package
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2019-01-26 https://doi.org/10.14419/ijet.v8i1.9.26391 -
Text Segmentation, MSER, image processing, food package -
Abstract
Many technologies help people with vision disabilities. It helps these people to walk, read, and other activities. However, when these people have to shop and there is no one to help, they can’t determine what product in their hand is. In this research, we applied image processing to recognize the name of the product based on text in the food package. We applied Maximally Stable Extremal Region (MSER) for text segmentation in the food package. The model is applied to predict the result of implementation MSER for text segmentation in the food package. We implement MSER with input from camera board in Raspberry Pi. Light intensity and type of food package give a different result. The result of this research has average 85%. It shows that MSER works for text segmentation in the food package.
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References
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How to Cite
Ike Sari, M., Handayani, R., & Maulana, S. (2019). Implementation of Maximally Stable Extremal Region for Text Segmentation on Food Package. International Journal of Engineering & Technology, 8(1.9), 157-160. https://doi.org/10.14419/ijet.v8i1.9.26391Received date: 2019-01-22
Accepted date: 2019-01-22
Published date: 2019-01-26