Abstract
An Intelligent Transportation System (ITS) is a new system developed for the betterment of user in traffic and transport management domain area for smart and safe driving. ITS subsystems are Emergency vehicle notification systems, Automatic road enforcement, Collision avoidance systems, Automatic parking, Map database management, etc. Advance Driver Assists System (ADAS) belongs to ITS which provides alert or warning or information to the user during driving. The proposed method uses Gaussian filtering and Median filtering to remove noise in the image. Subsequently image subtraction is achieved by subtracting Median filtered image from Gaussian filtered image. The resultant image is converted to binary image and the regions are analyzed using connected component approach. The prior work on speed bump detection is achieved using sensors which are failed to detect speed bumps that are constructed with small height and the detection rate is affected due to erroneous identification. And the smartphone and accelerometer methodologies are not perfectly suitable for real time scenario due to GPS error, network overload, real-time delay, accuracy and battery running out. The proposed system goes very well for the roads which are constructed with proper painting irrespective of their dimension.
Highlights
Driver assistance system is an important module in Intelligent Transportation System (ITS)
In addition to that here we focused on obstacle detection in road side like speed bump, poth holes, etc
In paper [4] [5] the speed bump detection is done with bump recorder, pedometer, three-dimensional gyro sensor and GPS
Summary
Driver assistance system is an important module in Intelligent Transportation System (ITS). The system is developed to alert a driver or to interact directly on the vehicle for safety and better driving. In addition to that here we focused on obstacle detection in road side like speed bump, poth holes, etc. We develop a system that services the end user driver using image processing concepts—Gaussian filtering, Median filtering and Connected Component Approach. The earlier approach of speed bump detection is achieved using dedicated sensors, three-axis accelerometer, Smart Phone and Image Processing. The system built with set of sensors embedded in vehicles to collect and process data and send it to portal based upon the continuous queries which are processed by continuous query processor on remote nodes. In paper [4] [5] the speed bump detection is done with bump recorder, pedometer, three-dimensional gyro sensor and GPS. The drawback of using sensor is miss classification of speed bump
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