Authors:
Eva T. Roca, Ezekiel Jacob P. Sikat, Trixxie Margarette F. Garcia, Az-Zubair J. Ahmadul, Irish Yari H. Virata, Reese Ivan A. Billanes and Reese David P. Larrauri |
Abstract:
In contemporary society, the demands on parents' time made it challenging to engage in regular reading
sessions with their children. In an effort to address this problem, this study created a text recognition reader
for kids which used Raspberry Pi as the main component. The Raspberry Pi, a single-board computer that
contains hardware components and sensor and controller interfaces that have user-friendly programming
capabilities, high connectivity, and desktop functionality, was used to run the script that will capture an image
from a webcam, binarize the captured frame, recognize the text, synthesize a voice using a reference, perform
text-to-speech with the synthesized voice, and output the sound through a Bluetooth speaker. The Text
Recognition Reader’s results revealed that it was less accurate in detecting text from a raw image and more
accurate when detecting text from a pre-preprocessed image. The Text Recognition Reader was also faster in
detecting text from a pre-processed image, getting an average of 1.03 seconds, than a raw image, getting an
average of 1.56 seconds. Given 50-word, 75-word, and 100-word reference text, the Text Recognition Reader
was able to synthesize a voice with averages of 61.07 seconds, 81.70 seconds, and 106.6 seconds respectively.
The Text Recognition Reader works more effectively and efficiently when working with pre-processed
images than raw images in terms of both text detection accuracy and speed. It was also found that the
processing time for voice synthesis heightened whenever the number of characters used in the utilized
reference text increased. The Text Recognition Reader was able to detect text, synthesize a voice using the
detected text, and read it out loud using the processed voice but also faced limitations. The Reader is highly
sensitive to the lighting conditions of its environment. |
Keywords:
Optical Character Recognition, Processing Time, Raspberry Pi, Text Recognition Reader, and Voice Synthesis. |
