Name
Title | ||
|---|---|---|
Hardware implementation of a spline-based genetic algorithm for embedded stereo vision sensor providing real-time visual guidance to the visually impaired |
Abstract | ||
|---|---|---|
Many image and signal processing techniques have been applied to medical and health care applications in recent years. In this paper, we present a robust signal processing approach that can be used to solve the correspondence problem for an embedded stereo vision sensor to provide real-time visual guidance to the visually impaired. This approach is based on our new one-dimensional (1D) spline-based genetic algorithm to match signals. The algorithm processes image data lines as 1D signals to generate a dense disparity map, from which 3D information can be extracted. With recent advances in electronics technology, this 1D signal matching technique can be implemented and executed in parallel in hardware such as field-programmable gate arrays (FPGAs) to provide real-time feedback about the environment to the user. In order to complement (not replace) traditional aids for the visually impaired such as canes and Seeing Eyes dogs, vision systems that provide guidance to the visually impaired must be affordable, easy to use, compact, and free from attributes that are awkward or embarrassing to the user. "Seeing Eye Glasses," an embedded stereo vision system utilizing our new algorithm, meets all these requirements. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1155/2008/385827 | EURASIP J. Adv. Sig. Proc. |
Keywords | Field | DocType |
spline-based genetic algorithm,robust signal processing approach,embedded stereo vision sensor,real-time visual guidance,seeing eye glasses,hardware implementation,signal processing technique,new algorithm,vision system,image data line,embedded stereo vision system,new one-dimensional,stereo vision | Signal processing,Computer vision,Image sensor,Machine vision,Computer science,Stereoscopy,Stereopsis,Image processing,Artificial intelligence,Correspondence problem,Computer hardware,Genetic algorithm | Journal |
Volume | Issue | ISSN |
2008, | 1 | 1687-6180 |
Citations | PageRank | References |
2 | 0.39 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dah-Jye Lee | 1 | 422 | 42.05 |
| Jonathan D. Anderson | 2 | 2 | 0.39 |
| James K. Archibald | 3 | 632 | 161.01 |