Implementation of Maximally Stable Extremal Region for Text Segmentation on Food Package - Ike Sari, Marlindia; Handayani, Rini; Maulana, Sidiq (International Journal of Engineering and Technology, 2019)
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 canâ€™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.Â