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|Title:||Road sign recognition for assisting drivers||Authors:||Poon, Wai Chung||Keywords:||DRNTU::Engineering||Issue Date:||2016||Abstract:||For a highly reliable autonomous vehicle, it must be able to detect traffic signs and obey the traffic rules. In this paper, color segmentation is applied in YCbCr color space and shape detection is processed through blob analysis method. By calculating the circularity and area ratio with bounding box, the shapes in binary images can be classified accurately. In the recognition stage, SURF algorithm is performed on both the training sets and sample images to extract the features points of the traffic signs for matching based on K-NN classifier.||URI:||http://hdl.handle.net/10356/67956||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Student Reports (FYP/IA/PA/PI)|
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