Identification Classification and Monitoring of Traffic Sign Using HOG and Neural Networks
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 8)Publication Date: 2015-08-05
Authors : Karthik B; Hari Krishna Murthy; Mukul Manohar;
Page : 782-786
Keywords : Traffic sign; Histogram of Orient Gradient HOG; Support Vector Machine SVM; Artificial Neural Network ANN;
Abstract
When the driving safety is considered, Identification of Traffic sign plays a major role which results in reducing the accidents. The recognition of traffic sign can also be used in Self driving intelligent cars. This paper represents a method to Identify the Traffic sign Patterns using Histogram of Oriented Gradients and Neural Network. Initially a classification of traffic sign is done by using HOG based Support Vector Machine. Secondly the classified data is used to train the Neural Network so that the neural networks are used to recognize the traffic sign patterns.16 different traffic sign image is taken to classify. To check the robustness of this system it was tested against 2, 946 images. It was found that accuracy of recognition was 98 % which indicates clearly the high robustness of the system.
Other Latest Articles
- Intelligent Secure System
- Autism Interactive System
- Study of Visual Outcome after Excision and Conjuctival Grafting as a Primary Procedure
- Marginal Adaptation of Calcium Silicate-based Materials used in Furcal Perforation Repair: A Comparative in Vitro Study
- A Review on Performance Improvement Techniques in Wireless Optical Communication
Last modified: 2021-06-30 21:52:09