A Access Traffic Sign Detection Tracking and Recognition System for Video Frames using KNN Algorithms
D. Siva Reddy1, Christeena Joseph2
1D. Siva Reddy, Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences, Chennai (Tamil Nadu), India.
2Christeena Joseph, Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences, Chennai (Tamil Nadu), India.
Manuscript received on 08 September 2019 | Revised Manuscript received on 17 September 2019 | Manuscript Published on 11 October 2019 | PP: 56-61 | Volume-8 Issue-11S September 2019 | Retrieval Number: K101209811S19/2019©BEIESP | DOI: 10.35940/ijitee.K1012.09811S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Video-based traffic sign detectiontracking and recognition plays an important role in driving support system as well as in intelligent autonomous vehicles. This framework includes three parts like traffic sign detecting, target tracking and sign recognition. This paper contributes different methods for detecting and recognizing of traffic sign, so that drivers can be easily identify the type of signal in road sides. In this approach different methods like color segmentation and scale based intraframe fusion technics is proposed which includes the spatial-temperol constraints in videos, by fusing the different casings that have a place with an equivalent physical sign along to induce higher exactness.
Keywords: Traffic Sign Detection, Tracking, Recognition, Kalman Filter.
Scope of the Article: Pattern Recognition