Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 7, Pages: 1-6
Nasrabadi Abbas1* and Vaezi Mahdi2
1Mechatronics Engineering Department, Computer and Electrical Engineering Faculty, Hakim Sabzevari University, Sabzevar, Iran 2Science and Research Branch of Azad University, Computer and Mechatronics Faculty, Tehran, Iran; [email protected]
*Author for Correspondence
Mechatronics Engineering Department, Computer and Electrical Engineering Faculty, Hakim Sabzevari University, Sabzevar, Iran [email protected]
Background: The dramatic increase in the traffic needs effective management that leads to the creation of intelligent transportation systems (ITS) or smart roads. Method: In this paper, a novel and quickly executable neural networks based method is presented to decide the configuration of an adaptive filter and choose among many possible segments of image. Findings: The trained network can be put in practice easily, a number of test image are presented to the software, and the program calculates the multiplication of each scene’s entropy and histogram average and based on that the trained radial basis network predicts the suitable filtering parameter. Result show the outcome of the network trial on three examples. It’s obviously because that the current input has values which are relatively close to the values put at the training stage. Applications/Improvements: A lot of research can be committed about enhanced filtering and masking ideas. A human operator is needed to approve the output’s readiness to be segmented.
Keywords: Color Filtering, Image Entropy, Machine Vision, Neural Networks, Online Road Detection
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