Traffic sign detection using fpga

Özkan, İbrahim
In this thesis, real time detection of traffic signs using FPGA hardware is presented. Traffic signs have distinctive color and shape properties. Therefore, color and shape based algorithms are chosen to implemented on FPGA. FPGA supports sufficient logic to implement complete systems and sub-systems. Color information of images/frames is used to minimize the search domain of detection process. Using FPGA, real time conversion of YUV space to RGB space is performed. Furthermore, color thresholding algorithm is used to localize the sign in the image/video depending on the color. Edges are the most important image/frame attributes that provide valuable information about the shape of the objects. Sobel edge detection algorithm is implemented on FPGA. After color segmentation, FPGA implementation of Sobel algorithm is used to find the edges of candidate traffic signs in real time. Later, radial symmetry based shape detection algorithm is used to determine circular traffic signs. Each FPGA implemented algorithm is tested by using video sequences and static images. In addition, combined implementation of color based and shape based algorithms are tested. Joint application of color and shape based algorithms are used in order to reduce search domain and the processing time of detection process. Designing architecture on FPGA makes traffic sign detection system portable as a final product and relatively more efficient than the computer based detection systems. The resulting hardware is suitable where cost and compactness constraints are important.


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Türk, Fethi; Bilgen, Semih; Department of Electrical and Electronics Engineering (2008)
Performance of neural network based restoration of optical networks is evaluated and a few possible improvements are proposed. Neural network based restoration is simulated with optical link capacities assigned by a new method. Two new improvement methods are developed to reduce the neural network size and the restoration time of severed optical connections. Cycle based restoration is suggested, which reduces the neural network structure by restoring the severed connections for each optical node, iterativel...
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Çifçi, Barış; Atalay, Aydın; Department of Electrical and Electronics Engineering (2006)
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Temiz, Yüksel; Akın, Tayfun; Department of Electrical and Electronics Engineering (2007)
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Frequency invariant beamforming and its application to wideband direction of arrival estimation
Babataş, Eren; Candan, Çağatay; Department of Electrical and Electronics Engineering (2008)
In this thesis the direction of arrival estimation of wideband signals using frequency invariant beamforming method is examined. The difficulty with the direction of arrival estimation of wideband signals is that it is not possible to obtain a single covariance matrix valid for the whole frequency spectrum of the signal. There are various methods proposed in the literature to overcome this difficulty. The common aim of all the methods is to obtain a composite covariance matrix for the overall band of the si...
Digital modulation recognition
Erdem, Erem; Tanık, Yalçın; Department of Electrical and Electronics Engineering (2009)
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Citation Formats
İ. Özkan, “Traffic sign detection using fpga,” M.S. - Master of Science, Middle East Technical University, 2010.