| Summary: | 碩士 === 國立交通大學 === 電機與控制工程系 === 87 === In this thesis, the hue, saturation, intensity (HSI) coordinate system and saturation enhancement are used to get the better segmentation between the traffic sign and other objects in the
image. The conventional pattern recognition methods only extract the feature vectors which are invariant to translation, rotation, and scale but are not invariant to distortion or occlusion in outdoor environment. This thesis describes a traffic sign recognition system capable of tolerating the above variations. The feature extraction is based on the techniques of the Fourier transform, Log-polar transform, and the of the discrete cosine transform (DCT). Because of the energy compaction of DCT, the DCT can be used as feature extraction for shape recognition. The features are used as the inputs of the neural network which is a classifier. The performance of the proposed system is evaluated by examining the effect of
various conditions which may occur in natural outdoor environment.
|
|---|
