A noise-tolerant traffic sign recognition method based on color images /
backpropagation neural network trained by using signatures of
| Main Author: | |
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| Format: | Thesis eBook |
| Language: | English |
| Published: |
[Place of publication not identified] :
[publisher not identified] ;
1995.
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| Subjects: | |
| Online Access: | Link to OAKTrust copy |
| Summary: | backpropagation neural network trained by using signatures of challenging problem. Such a method has to cope with conditions that can be expected in realistic environments. Devising a pattern recognition methodology for traffic sign exponential grid and Fourier transformations. Finally, a giving the best separation between traffic signs and other images captured in noisy outdoor environments poses a ISH, XYZ, YIQ, uvY) is evaluated via several separability measures in order to obtain the color coordinate system object, with centroid noise as when an interfering object is objects in the scene. Color segmentation is performed by occlusion noise as when part of the region of interest (in present in the vicinity of the region of interest, etc. In scale, location, and orientation based on the log polar segmented binary image of the traffic sign. A signature of signs. The performance of various color coordinate systems (RGB, the recognition rate will not be adversely affected by noisy the traffic sign is extracted that is invariant to changes in this case, the traffic sign) is blocked by an interfering this research, a noise-tolerant method is designed such that using a self-organizing neural network, which generates a various traffic sign images is used to classify the traffic |
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| Item Description: | "Major subject: Electrical Engineering". Vita. |
| Physical Description: | xii, 82 leaves : illustrations ; 28 cm. Also available online. Issued also on microfiche from Lange Micrographics. |
| Bibliography: | Includes bibliographical references. |