Speed Limit Traffic Sign Classification Using Multiple Features Matching

Soetedjo, Aryuanto (2017) Speed Limit Traffic Sign Classification Using Multiple Features Matching. In: Speed Limit Traffic Sign Classification, September 25-28, Bali.

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Abstract

This paper presents the method to classify the speed limit traffic sign using multiple features, namely histogram of oriented gradient (HOG) and maximally stable extremal regions (MSER) features. The classification process is divided into the outer circular ring matching and the inner part matching. The HOG feature is employed to match the outer circular ring of the sign, while MSER feature is employed to extract the digit number in the inner part of the sign. Both features are extracted from the grayscale image. The algorithm detects the rotation angle of the sign by analyzing the blobs which is extracted using MSER. In the matching process, tested images are matched with the standard reference images by calculating the Euclidean distance. The experimental results show that the proposed method for matching the outer circular ring works properly to recognize the circular sign. Further, the digit number matching achieves the high classification rate of 93.67% for classifying the normal and rotated speed limit signs. The total execution time for classifying six types of speed limit sign is 10.75 ms. Keywords: Speed limit traffic sign � HOG � MSER � Template matching

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Speed limit traffic sign � HOG � MSER � Template matching
Subjects:	Engineering > Electrical Engineering
Divisions:	Fakultas Teknologi Industri > Teknik Elektro S1
Depositing User:	Ms Nunuk Yuli
Date Deposited:	10 Feb 2021 05:33
Last Modified:	07 Dec 2021 04:04
URI:	http://eprints.itn.ac.id/id/eprint/5326

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