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REAL TIME MOVING VEHICLE DETECTION BY USING HAAR CASCADE CLASSIFIER

  • Unique Paper ID: 164025
  • Volume: 10
  • Issue: 12
  • PageNo: 970-974
  • Abstract:
  • Vehicle detection plays a crucial role in various real time applications including Traffic Monitoring, Security , Robotics , Surveillance and Autonomous driving system and Automotive industry. In this project we are using open-cv for image processing and Haar Cascade Classifier which is used for vehicle detection. The Haar Cascade Classifier is a machine learning based approach capable of detecting objects in images with high accuracy and better efficiency .We can also create our own customized haar cascade classifier. In the process of moving vehicle detection involves capturing video frames from a camera feed in real time ,pre-processing the frames to enhance features and apply the Haar Cascade Classifier to detect the vehicles .In data collection ,Gather a large dataset of positive and negative images Positive images contain the objects what we want to detect(example.. vehicles),while the negative images contains the unwanted data( it does not contain any instance of object).After data collection we will convert the image in to gray scale and potentially applying other preprocessing techniques like histogram equalization to enhance the contrast. All the negative images are filtered (removed) by the step pre-processing.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 970-974

REAL TIME MOVING VEHICLE DETECTION BY USING HAAR CASCADE CLASSIFIER

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