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Title: Computational vision applied in automotive driving support systems
Authors: Aldwihe, Ramez
Saias, José
Keywords: Image Processing
Traffic sign detection
Issue Date: 27-Oct-2017
Publisher: Instituto Politécnico de Beja
Citation: Aldwihe and Saias (2017). Computational vision applied in automotive driving support systems. In IV Workshop on Computational Data Analysis and Numerical Methods (Book of Abstracts). ISBN: 978-989-8008-29-9. Beja, Portugal
Abstract: The objectives of this work are: to build a system which recognizes traffic signs by analyzing the images/video taken with a camera installed in the car. The system includes three stages: Detection, Classification, and Recognition. The data set which I used to train and to test the model is German Traffic Sign Recognition Benchmark (GTSRB) data set [1], a publicly available data set for single-image. The system also used with Portuguese traffic signs database and several examples taken from Portuguese roads are used to demonstrate the effectiveness of the proposed system. Traffic signs are detected by analyzing color information, red and blue, and analyzing the shape of the signs as triangular, squared and circular shapes, contained in the images using Opencv library. To make the classifier, I used Convolutional Neural Network technique with TensorFlow as a Machine Learning framework. The recognition of traffic signs is done by comparing the data from classification phase with the ones of the database. The results in the classifier are almost 97,7 % [2], and results in detection part are 70% for red and blue traffic signs respectively.
Type: lecture
Appears in Collections:INF - Comunicações - Em Congressos Científicos Nacionais

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