Braille Character Recognition Using Find Contour And Artificial Neural Network

Joko Subur, Tri Arief Sardjono, Ronny Mardiyanto


Abstract—Braille letters is characters designed for the blind, composed of six embossed points, arranged in a standard braille character. Braille letters is touched and read using fingers, therefore the sensitivity of the fingers is important. Those characters need to be memorized, so it is very difficult to be learned. The aim of this research is to create a braille characters recognition system and translate it to alpha-numeric text. Webcam camera is used to capture braille image from braille characters on the paper sheet. Cropping, grayscale, thresholding, erotion, and dilation techniques are used for image preprocessing. Then, find contour and artificial neural network method are used to recognize the braille characters. The system can recognize braille characters with 99% accuracy even when the braille image is tilted up to 1 degrees.


Keywords— Artifial neural network; braille characters; find contour; image processing; webcam

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