Decimal Digits Recognition from Lip Movement Using GoogleNet network
Lip reading is a visual way to communicate with people through the movement of the lips, especially the
hearing impaired and people who are in noisy environments such as stadiums and airports. Lip reading is
not easy to face many difficulties, especially when taking a video of the person, including lighting,
rotation, the person’s position and different skin colors...etc. As researchers are constantly looking for
new techniques for lip-reading.
The main objective of the paper is to design and implement an effective system for identifying decimal
digits by movement. Our proposed system consists of two stages, namely, preprocessing, in which the
face and mouth area are detected, lips are determined and stored in a temporary folder to used viola jones.
The second stage is to take a GoogleNet neural network and insert the flange frame in it, where the
features will be extracted in the convolutional layer and then the classification process where the results
were convincing and we obtained an accuracy of 87% by using a database consisting of 35 videos and it
contained seven males and two females, and the number of the frame was 21,501 lips image.
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