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Braille is the language of communication for blind and visually impaired people. Braille characters are embossed at points to convey the meaning. Typically, Braille documents can be produced on plain paper. Braille documents can be created on reusable paper, also known as a third-page paper; this reduces the paper cost, allowing more available documents to stimulate learning for blind or visually impaired persons. This research presents a method of Braille embossed dots segmentation for Braille document images produced on reusable paper to support the availability of cheaper learning material. Initially, Braille documents were imported with a calibrated scanner, Braille document image layer separation was then performed. Followed by edge removal, Braille embossed dot recovery, noise removal, and specify the embossed Braille point. This research was conducted by using four scanners, which scanned Braille documents images under four different lighting conditions. For each lighting condition, the Braille document image area was cropped to the desired size, considering the possible event conditions. They were used to create over 200,000 Braille cells, with over 12 billion patterns. When calculating the average performance under all lighting conditions, the values were Precision 1.0000, Recall 0.7817, Accuracy 0.8545, and F-Measure 0.8756. By effectively using Braille embossed dots segmentation, the process of Braille document recognition will also be efficient.

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