Camera Recognition Based American Sign Language Translator

Overview

Objectives/Goals The design and construction of an American Sign Language-to-text translator for sign language users to communicate to anyone. My approach to this conundrum is to use a relative inexpensive camera, take a picture of the user#s hand, map the position of the fingertips and then determine the distances in between the fingertips. These distance values can then be correlated to values stored in a database and assigned an alphabet character. The software in questions is written in C# with a clear and concise visual GUI to allow for fine-tuning at a testing level and future expansion towards an end-user application. Methods/Materials The goal behind this project was to maintain a definitive ease of use and simplicity of the implementation. This was done by using an extremely affordable PC webcam and (besides the computer /w software) no other physical components. The software#s approach maintains simplicity to allow it to be hosted by low-power, handheld platforms. After the camera took a picture of the end-user#s hand, the software determined the relative distances in-between the user#s fingertips. This was done so regardless of how the user rotated his hand (relative to the camera) the relative distances between the user#s fingertips remained constant. Results Through several trial runs of the system, the camera and software were successfully able to read-in and output the matching hand-sign alphabet. However, it is to be noted that these trials were conducted in a controlled environment (with controlled lightning and background) and not out in the field. Conclusions/Discussion Along with creating an effective end-user product, this project has opened many possibilities for future development and expansion. For example, making the software adaptive to the end-user#s physical limitations (i.e. hand size) and perhaps making it aware of the hand-signers individual style and technique.

Competition history

• CSEF 2009 Mathematics & Software · Entry S1606

Resources

• CSEF project summary ↗

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