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Information Journal Paper

Title

TRAFFIC ROAD SIGN DETECTION AND CLASSIFICATION

Pages

  54-62

Abstract

 Traffic ROAD SIGN DETECTION is important to a robotic vehicle that automatically drives on roads. As the colors of most traffic road signs are blue and red, in this paper, we use Hue- Saturation- Intensity (HSI) color space for color based segmentation at first. Using important geometrical features, the road signs are detected perfectly. After segmentation, it turns to classify every detected road signs. For this purpose, we employ and compare the performance of three classifiers; they are distance to border (DTB), FFT sample of signature, and CODE MATRIX. In this work, we use the CODE MATRIX as an efficient classifier for the first time. Although the achieved accuracy by CODE MATRIX is greater than the two referred classifiers in average, the main advantage is simplicity and so less computational cost.

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    • Cite

    APA: Copy

    FARTAJ, MEHDI, & GHOFRANI, SEDIGHEH. (2012). TRAFFIC ROAD SIGN DETECTION AND CLASSIFICATION. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, 6(4 (23)), 54-62. SID. https://sid.ir/paper/624848/en

    Vancouver: Copy

    FARTAJ MEHDI, GHOFRANI SEDIGHEH. TRAFFIC ROAD SIGN DETECTION AND CLASSIFICATION. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2012;6(4 (23)):54-62. Available from: https://sid.ir/paper/624848/en

    IEEE: Copy

    MEHDI FARTAJ, and SEDIGHEH GHOFRANI, “TRAFFIC ROAD SIGN DETECTION AND CLASSIFICATION,” MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, vol. 6, no. 4 (23), pp. 54–62, 2012, [Online]. Available: https://sid.ir/paper/624848/en

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