Research Article Open Access

An Improved Approach for Detecting Car in Video using Neural Network Model

T. Senthil Kumar1 and S. N. Sivanandam2
  • 1 , India
  • 2 Karpagam College of Engineering, India

Abstract

The study represents a novel approach taken towards car detection, feature extraction and classification in a video. Though many methods have been proposed to deal with individual features of a vehicle, like edge, license plate, corners, no system has been implemented to combine features. Combination of four unique features, namely, color, shape, number plate and logo gives the application a stronghold on various applications like surveillance recording to detect accident percentage(for every make of a company), authentication of a car in the Parliament(for high security), learning system(readily available knowledge for automobile tyro enthusiasts) with increased accuracy of matching. Video surveillance is a security solution for government buildings, facilities and operations. Installing this system can enhance existing security systems or help start a comprehensive security solution that can keep the building, employees and records safe. The system uses a Haar cascaded classifier to detect a car in a video and implements an efficient algorithm to extract the color of it along with the confidence rating. An gadabouts trained classifier is used to detect the logo (Suzuki/Toyota/Hyunadai) of the car whose accuracy is enhanced by implementing SURF matching. A combination of blobs and contour tracing is applied for shape detection and model classification while number plate detection is performed in a smart and efficient algorithm which uses morphological operations and contour tracing. Finally, a trained, single perceptron neural network model is integrated with the system for identifying the make of the car. A thorough work on the system has proved it to be efficient and accurate, under different illumination conditions, when tested with a huge dataset which has been collected over a period of six months.

Journal of Computer Science
Volume 8 No. 10, 2012, 1759-1768

DOI: https://doi.org/10.3844/jcssp.2012.1759.1768

Submitted On: 11 June 2012 Published On: 1 September 2012

How to Cite: Kumar, T. S. & Sivanandam, S. N. (2012). An Improved Approach for Detecting Car in Video using Neural Network Model. Journal of Computer Science, 8(10), 1759-1768. https://doi.org/10.3844/jcssp.2012.1759.1768

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Keywords

  • Different classes
  • analysis
  • bias function
  • neural networks
  • dimensionality
  • feature
  • SURF