کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6900448 1446489 2018 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Traffic Sign Recognition Based On Multi-feature Fusion and ELM Classifier
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
Traffic Sign Recognition Based On Multi-feature Fusion and ELM Classifier
چکیده انگلیسی
This paper proposes a novel and efficient method for traffic sign recognition based on combination of complementary and discriminative feature sets. The extracted features are the histogram of oriented gradients (HOG) feature, Gabor feature and Compound local binary pattern (CLBP) feature. The classification is performed using the extreme learning machine (ELM) algorithm. Performances of the proposed approach are evaluated on both German Traffic Sign Recognition Benchmark (GTSRB) and Belgium Traffic Sign Classification (BTSC) Datasets respectively. The results of the experimental work demonstrate that each feature yields fairly high accuracy and the combination of three features has shown good complementariness and yielded fast recognition rate and is more adequate for real-time application as well.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 127, 2018, Pages 146-153
نویسندگان
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