Abstract
This paper presents the results of our research in automatic recognition of the Mexican Sign Language (MSL) alphabet as control element for a service robot. The technique of active contours was used for image segmentation in order to recognize de signs. Once segmented, we proceeded to obtain the signature of the corresponding sign and trained a neural network for its recognition. Every symbol of the MSL was assigned to a task that the robotic system had to perform; we defined eight different tasks. The system was validated using a simulation environment and a real system. For the real case, we used a mobile platform (Powerbot) equipped with a manipulator with 6 degrees of freedom (PowerCube). For simulation of the mobile platforms, RoboWorks was used as the simulation environment. In both, simulated and real platforms, tests were performed with different images to those learned by the system, obtaining in both cases a recognition rate of 95.8%.
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Luis-Pérez, F.E., Trujillo-Romero, F., Martínez-Velazco, W. (2011). Control of a Service Robot Using the Mexican Sign Language. In: Batyrshin, I., Sidorov, G. (eds) Advances in Soft Computing. MICAI 2011. Lecture Notes in Computer Science(), vol 7095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25330-0_37
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DOI: https://doi.org/10.1007/978-3-642-25330-0_37
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