Optical correlator based Traffic Signs Inventory system

Harasthy, T.; Turán, Ján; Ovseník, Ľuboš

doi:10.1109/iwssip.2013.6623463

Cited by 2 publications

(5 citation statements)

References 6 publications

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“…Fig. 2 illustrates the block diagram of Preprocessing [5][6][7][8]. 2) Colour filtering: In this subblock there is colour filters on a modified image applied.…”

Section: B Input Scene Processingmentioning

confidence: 99%

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Inventory System of Vertical Traffic Signs

Solus

Ovseník

Turán

2015

2015 25th International Conference Radioelektronika (RADIOELEKTRONIKA)

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Control systems in general are very important in these days. There are used in many industrial fields such as automotive, medicine and manufacture. This paper contains a draft of VTSIS (Vertical Traffic Signs Inventory System). VTSIS has wide application in the control of traffic signs, which number is increasing annually. Cambridge optical correlator is used in designed inventory system as comparator. The use of optical processing technology will increase the speed of processing amounts of data.

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“…Fig. 2 illustrates the block diagram of Preprocessing [5][6][7][8]. 2) Colour filtering: In this subblock there is colour filters on a modified image applied.…”

Section: B Input Scene Processingmentioning

confidence: 99%

“…The largest of them is the input image. Created scene is sent to the input of Cambridge optical correlator [7].…”

Section: ) Region Of Interest -Roimentioning

confidence: 99%

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Inventory System of Vertical Traffic Signs

Solus

Ovseník

Turán

2015

2015 25th International Conference Radioelektronika (RADIOELEKTRONIKA)

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“…As a result, computation time can be reduced, significantly. For segmentation purpose, mostly RGB [4][8] [12] and HSI/HSV [7][9][10] [13] color spaces are preferred. On the other hand, spaces like L*a*b* [11] and YC B C R [21] are also employed.…”

Section: Background Of Traffic Sign Detection and Recognitionmentioning

confidence: 99%

“…Comparing unknown sign and templates in the database several methods are used in literature. Khan et al [11] and Harasthy et al [13] prefer to use Fourier transform. In [11], a joint image is generated by putting input scene and template side-by-side, then Fourier transform is applied to joint image.…”

Section: Background Of Traffic Sign Detection and Recognitionmentioning

confidence: 99%

Real-time Traffic Sign detection and Recognition on FPGA

Yalçın

Irmak

Bulut

et al. 2013

2013 21st Signal Processing and Communications Applications Conference (SIU)

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In this thesis, an embedded system for traffic sign detection and recognition is proposed. Proposed system is first designed in MATLAB and optimized. After optimization process, system design is transferred to FPGA and Virtex-V FX70 FPGA is selected for implementation platform. 640x480 sized image in RGB format is sent to FPGA system via computer interface. This image is segmented for red, blue, and yellow colors. Red and blue color maps are divided into 8x8 sub-blocks. Yellow color map is divided into 32x32 sub-blocks. After that, blocks which have more than 30 % valid pixels are marked as valid. Red and blue maps are converted into 80x60 and blobs are detected in these maps. Size of the detected blob is examined first and appropriate sized regions are marked as valid. Next, to be marked as traffic sign, valid regions are expected to meet one of the three conditions: Vertical neighboring, yellow sign neighboring and pole detection below the region. Regions marked as traffic sign are interpolated to 60x60. Color segmentation operation is applied to these regions and edges are extracted in segmented images. Hough Transform is applied to edge images and contour information is extracted. Finally, Informative Pixel Percentage (IPP) operation is applied to inner region of the signs and results are obtained. FPGA system is composed of two sub-parts: Processor system and hardware (logic) system. Color segmentation, region detection and pole detection modules are implemented in hardware system. Rest of the operations is implemented in the processor system. To test success of the implemented system, 137 images, which include 162 traffic signs, are sent to this system and 90.1 % detection and 90.4 % recognition rates are achieved.

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Optical correlator based Traffic Signs Inventory system

Cited by 2 publications

References 6 publications

Inventory System of Vertical Traffic Signs

Inventory System of Vertical Traffic Signs

Real-time Traffic Sign detection and Recognition on FPGA

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