Received Date : 02-June-2017
Published Online: 01-September-2017
FIGURES & TABLES
This paper presents a technique to classify the circular traffic sign based-on HOG (histogram of oriented gradients) and a ring partitioned matching. The method divides an image into several ring areas, and calculates the HOG feature on each ring area. In the matching process, the weight is assigned to each ring for calculating the distance of HOG feature between tested image and reference image. The experimental results show that the proposed algorithm achieves a high classification rate of 97.8%, without the need of many prepared sample images. The results also show that the best values of the number of orientation bins and the cell size of the HOG parameters are 5 and 10 x 10 pixels respectively.
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Soetedjo,A., & Somawirata,I.K.(2017).CIRCULAR TRAFFIC SIGN CLASSIFICATION USING HOGBASED RING PARTITIONED MATCHING.International Journal on Smart Sensing and Intelligent Systems, 10(3), 735-753.doi:10.21307/ijssis-2017-232.
Soetedjo,Aryuanto., and I Komang Somawirata"CIRCULAR TRAFFIC SIGN CLASSIFICATION USING HOGBASED RING PARTITIONED MATCHING"International Journal on Smart Sensing and Intelligent Systems 10,no.3(2017):735-753doi:10.21307/ijssis-2017-232.
Soetedjo,Aryuanto., and I Komang Somawirata"CIRCULAR TRAFFIC SIGN CLASSIFICATION USING HOGBASED RING PARTITIONED MATCHING"International Journal on Smart Sensing and Intelligent Systems 10.no.3(2017):735-753doi:10.21307/ijssis-2017-232.
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