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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In this thesis, a new algorithm is proposed for the recognition of triangular, circular and rectangular traffic signs and it is implemented on an FPGA platform. The system can recognize 32 different traffic signs with high recognition accuracy. In the proposed method, first the image is segmented into red and blue regions, and according to the area of the each segment, the dominant color is decided. Then, Laplacian of Gaussian (LoG) based edge detection is applied to the segmented image which is followed by Hough Transform for shape extraction. Then, recognition based on Informative Pixel Percentage (IPP) matching is executed on the extracted shapes. The Traffic Sign Recognition (TSR) system is implemented on Virtex 5 FX70T FPGA, which has an embedded PPC440 processor. Some modules of TSR algorithm are designed in the FPGA logic while remaining modules are designed in the PPC440 processor. Work division between FPGA and PPC440 is carried out considering their capabilities and shortcomings of FPGA and processor. Benefits of using an FPGA with an embedded processor are exploited to optimize the system.

Graduate school has been a time of travel through experimentation. The journey has almost always been a search for materials and sources that match my need for working with the self-referential narrative within the framework of a process. Repeatedly, I would venture out and turn back, only to venture out again, packed with new materials and image sources, in search of a complete process. In retrospect, there have been no dead ends, only quenched curiosities that sometimes cleanly, often clumsily, lead one to the other. What is left is a series of explorations from which I can pluck similarities, clues to my core interests and methods. In the end, I believe I have found a place of clarity, where interests and process converge.

In this thesis, detection of traffic signs is studied. Since, both color and shape properties of traffic signs are distinctive / these two properties have been employed for detection. Detection using color properties is studied in two different color domains in order to examine and compare the advantages and the disadvantages of these domains for detection purposes. In addition to their color information, shape information is also employed for detection purpose. Edge information (obtained by using the Sobel Operator) of the images/frames is considered as search domain to find triangular, rectangular, octagonal and circular traffic signs. In order to improve the performance of detection process a joint implementation of shape and color based algorithms is utilized. Two different methods have been used v in order to combine these two features. Both of the algorithms help reducing the number of pixels to check whether they belong to a sign or not. This, of course, reduces the processing time of detection process. Each utilized algorithm is tested and compared with the others by using both static images from different sources and video streams. Images having adverse properties are used in order to state algorithms response for some specific conditions such as bad illumination and shadow. After implementation, results show that joint implementation of the color and shape based detection algorithms produces more accurate results. Moreover, joint implementation reduces the processing time of the detection process when compared to application of algorithms individually since it diminishes the search domain.