Real Time Road Sign Recognition System
Real Time Road Sign Recognition System Using Artificial Neural Networks For Bengali Textual Information Box
An Automated Road Sign Recognition system using Artificial Neural Network for the Textual Information box inscribing in Bengali is presented on the paper. Signs are visual languages that represent some special circumstantial information of environment. Road signs, being among the most important around us primarily for safety reasons, are designed, and manufactured and installed according to tight regulations. The system captures real time images every two seconds and saves them as JPG format files. Firstly some road sign are already stored in the memory. Like: Warning Sign, Prohibition Sign, Obligation Sign and Informative Sign. Car Driver concentration and illiterateness isn’t always focused on what it should be and not always notice the road signs. For these reasons, automation of Bangla Road Sign Recognition system is highly essential. Previously several works are done by Mueller, Piccioli, Novovicova, Yuille, Escalera and others. But those are not in Bengali. Real Time Road Sign Recognition System Using Artificial Neural Networks for Bengali Textual Information Box which is done by Mohammad Osiur Rahman, Fouzia Asharf Mousumi, Edgar Scavino, Aini Hussain, Hassan Basri whose are from the Department of Computer Science and Engineering, University of Chittagong, Chittagong-4331, Bangladesh, Faculty of Engineering, University Kebangsaan Malaysia. For doing this they divide the total Concept in Steps: 1. Image Acquisition: From several video sequences from a moving vehicle for a certain period are consecutive frames recorded within 2 seconds are similar. For this they have used Application Programming Interface functions of VB 6.0. Every 2-second a frame is collected and stored in JPG format.
2. Preprocessing: Median filter is used to reduce impulsive or salt-and-pepper type noise from captured images and then normalized into 320 X 240 pixels.
An Automated Road Sign Recognition system using Artificial Neural Network for the Textual Information box inscribing in Bengali is presented on the paper. Signs are visual languages that represent some special circumstantial information of environment. Road signs, being among the most important around us primarily for safety reasons, are designed, and manufactured and installed according to tight regulations. The system captures real time images every two seconds and saves them as JPG format files. Firstly some road sign are already stored in the memory. Like: Warning Sign, Prohibition Sign, Obligation Sign and Informative Sign. Car Driver concentration and illiterateness isn’t always focused on what it should be and not always notice the road signs. For these reasons, automation of Bangla Road Sign Recognition system is highly essential. Previously several works are done by Mueller, Piccioli, Novovicova, Yuille, Escalera and others. But those are not in Bengali. Real Time Road Sign Recognition System Using Artificial Neural Networks for Bengali Textual Information Box which is done by Mohammad Osiur Rahman, Fouzia Asharf Mousumi, Edgar Scavino, Aini Hussain, Hassan Basri whose are from the Department of Computer Science and Engineering, University of Chittagong, Chittagong-4331, Bangladesh, Faculty of Engineering, University Kebangsaan Malaysia. For doing this they divide the total Concept in Steps: 1. Image Acquisition: From several video sequences from a moving vehicle for a certain period are consecutive frames recorded within 2 seconds are similar. For this they have used Application Programming Interface functions of VB 6.0. Every 2-second a frame is collected and stored in JPG format.
2. Preprocessing: Median filter is used to reduce impulsive or salt-and-pepper type noise from captured images and then normalized into 320 X 240 pixels.