Helmet Detection on Two-Wheelers and Number Plate Recognition using Image Processing
C. Nikhita1, Chaithanya S.2, Deeksha P.3, Shyma Zaidi4
1C. Nikhita, Department of Electronics and Communication Engineering, Vidyavardhaka College of Engineering, Mysuru (Karnataka), India.
2Chaithanya S, Department of Electronics and Communication Engineering, Vidyavardhaka College of Engineering, Mysuru (Karnataka), India.
3Deeksha P, Department of Electronics and Communication Engineering, Vidyavardhaka College of Engineering, Mysuru (Karnataka), India.
4Shyma Zaidi, Department of Electronics and Communication Engineering, Vidyavardhaka College of Engineering, Mysuru (Karnataka), India.
Manuscript received on 24 August 2019 | Revised Manuscript received on 11 September 2019 | Manuscript Published on 17 September 2019 | PP: 1822-1824 | Volume-8 Issue-2S8 August 2019 | Retrieval Number: B11620882S819/2019©BEIESP | DOI: 10.35940/ijrte.B1162.0882S819
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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: There has been a sudden increase in motorcycle accidents over the years. The helmet is a safety equipment that protects the motorcyclists, however many riders (i.e. students) don’t use it and the results could be fatal. This paper holds an agenda to propose a system for detection of motorcyclists without helmet. The proposed idea first detects motorcycle riders using surveillance video using background subtraction and object segmentation methods. We have also used techniques that involve human face detection using image processing. This includes face detection using Haar like feature technique and circular Hough transform method that helps in detecting any circular object hence detecting the helmet. This approach works in the near real time mode with significantly low false alarms.
Keywords: Helmet Detection, Number Plate Recognition, Image Processing, Two Wheelers.
Scope of the Article: Image Processing and Pattern Recognition